This workshop will empower healthcare professionals with the knowledge and skills to leverage artificial intelligence (AI) in their practice. It aims to bridge the gap between cutting-edge technology and everyday clinical, research, and educational practice. The platforms covered in the workshop include Elicit.org, Scholarcy.com, Typeset.io, ChatGPT, Botpress.com, InVideo.io, and Genie.io.
The objectives of this specialised workshop are to:
• Explore the core principles of AI, emphasising its applications and significance in modern healthcare.
• Examine the role of AI in enhancing clinical judgment and patient management, with live demonstrations of relevant tools.
• Uncover the potential of AI in revolutionising teaching and learning experiences for healthcare professionals and students.
• Illustrate the integration of AI in healthcare research, focusing on tasks such as literature review, data analytics, and manuscript development.
• Provide a hands-on experience with various AI platforms tailored to healthcare professionals' unique needs and demands
5 Powerful Real World Examples Of How AI Is Being Used In HealthcareBernard Marr
Healthcare can be transformed with the innovation and insights of artificial intelligence and machine learning. From robot-assisted surgery to virtual nursing assistants, diagnosing conditions, facilitating workflow and analyzing images, AI and machines can help improve outcomes for patients and lower costs for providers.
Patients are about to see a new doctor: artificial intelligence by EntefyEntefy
The health care industry has already seen advanced artificial intelligent systems make an impact in areas like medical diagnosis and patient care. But the long-term big-picture importance of AI in medicine may be something else entirely: a potential fix for the intractable problem of too few doctors and nurses worldwide. And as part of that, a solution to health care’s public enemy number one—paperwork.
Entefy curated a presentation based on our article about the impact of artificial intelligence in medical care. These slides provide a snapshot of how AI is at use in medical care today, the advances and limits of current AI systems, and AI’s potential in patient care. The presentation contains useful data and analysis for anyone interested in the intersection of AI and medical care.
For additional analysis and links to our background sources, read “Patients are about to see a new doctor: artificial intelligence" on our blog at https://blog.entefy.com/view/298/Patients-are-about-to-see-a-new-doctor-artificial-intelligence.
Generative AI in Healthcare Market - Copy - Copy.pptxGayatriGadhave1
Generative AI holds significant promise in healthcare, there are also challenges related to data privacy, model interpretability, and regulatory compliance that need to be addressed. Ethical considerations and thorough validation processes are crucial to ensure the responsible and safe application of generative AI techniques in healthcare.
Artificial Intelligence is explained in detail. The following topics are covered in this video:
1. What Is Artificial Intelligence?
2. Types Of Artificial Intelligence
3. Applications Of Artificial Intelligence
Website: www.prishth.in
5 Powerful Real World Examples Of How AI Is Being Used In HealthcareBernard Marr
Healthcare can be transformed with the innovation and insights of artificial intelligence and machine learning. From robot-assisted surgery to virtual nursing assistants, diagnosing conditions, facilitating workflow and analyzing images, AI and machines can help improve outcomes for patients and lower costs for providers.
Patients are about to see a new doctor: artificial intelligence by EntefyEntefy
The health care industry has already seen advanced artificial intelligent systems make an impact in areas like medical diagnosis and patient care. But the long-term big-picture importance of AI in medicine may be something else entirely: a potential fix for the intractable problem of too few doctors and nurses worldwide. And as part of that, a solution to health care’s public enemy number one—paperwork.
Entefy curated a presentation based on our article about the impact of artificial intelligence in medical care. These slides provide a snapshot of how AI is at use in medical care today, the advances and limits of current AI systems, and AI’s potential in patient care. The presentation contains useful data and analysis for anyone interested in the intersection of AI and medical care.
For additional analysis and links to our background sources, read “Patients are about to see a new doctor: artificial intelligence" on our blog at https://blog.entefy.com/view/298/Patients-are-about-to-see-a-new-doctor-artificial-intelligence.
Generative AI in Healthcare Market - Copy - Copy.pptxGayatriGadhave1
Generative AI holds significant promise in healthcare, there are also challenges related to data privacy, model interpretability, and regulatory compliance that need to be addressed. Ethical considerations and thorough validation processes are crucial to ensure the responsible and safe application of generative AI techniques in healthcare.
Artificial Intelligence is explained in detail. The following topics are covered in this video:
1. What Is Artificial Intelligence?
2. Types Of Artificial Intelligence
3. Applications Of Artificial Intelligence
Website: www.prishth.in
Artificial intelligence enters the medical fieldRuchi Jain
In the medical and health field, artificial intelligence can help reduce the cost of ongoing health operations, and can have an impact on the quality of medical care for patients everywhere. By diagnosing diseases earlier, AI can also improve patient outcomes. No matter how you look at it, artificial intelligence has great potential in healthcare.
10 Common Applications of Artificial Intelligence in HealthcareTechtic Solutions
List of 10 Common Applications of Artificial Intelligence that explain how artificial intelligence is used in healthcare and why it is necessary? To read briefly all common applications of artificial intelligence in healthcare then visit at https://www.techtic.com/blog/applications-of-ai-in-healthcare/
AI and ML Series - Introduction to Generative AI and LLMs - Session 1DianaGray10
Session 1
👉This first session will cover an introduction to Generative AI & harnessing the power of large language models. The following topics will be discussed:
Introduction to Generative AI & harnessing the power of large language models.
What’s generative AI & what’s LLM.
How are we using it in our document understanding & communication mining models?
How to develop a trustworthy and unbiased AI model using LLM & GenAI.
Personal Intelligent Assistant
Speakers:
📌George Roth - AI Evangelist at UiPath
📌Sharon Palawandram - Senior Machine Learning Consultant @ Ashling Partners & UiPath MVP
📌Russel Alfeche - Technology Leader RPA @qBotica & UiPath MVP
Algorithmic Bias: Challenges and Opportunities for AI in HealthcareGregory Nelson
Gregory S. Nelson, VP, Analytics and Strategy – Vidant Health | Adjunct Faculty Duke University
The promise of AI is quickly becoming a reality for a number of industries including healthcare. For example, we have seen early successes in the augmenting clinical intelligence for diagnostic imaging and in early detection of pneumonia and sepsis. But what happens when the algorithms are biased? In this presentation, we will outline a framework for AI governance and discuss ways in which we can address algorithmic bias in machine learning.
Objective 1: Illustrate the issues of bias in AI through examples specific to healthcare.
Objective 2: Summarize the growing body of work in the legal, regulatory, and ethical oversight of AI models and the implications for healthcare.
Objective 3: Outline steps that we can take to establish an AI governance strategy for our organizations.
When it comes to AI use for prediction, diagnosis and treatment of medical conditions, reality is often replaced with a hype. Limitations should be known. A review of AI failures and challenges in healthcare showing why it is not likely for algorithms to replace physicians in the nearest future.
AI in Healthcare: From Hype to Impact (updated)Mei Chen, PhD
The primary goal of this workshop is to help health professionals gain a critical understanding of the various types of AI technologies available so they can make wise decisions and invest AI for healthcare improvement.
From traffic routing to self-driving cars, Alexa to Siri, AI’s reach is extending into all areas of life, including healthcare. Join Kimberley to learn more about how AI is being used now, and will be used in the near future, to facilitate provider-patient communication, mine medical records, assess patients, predict illness, suggest treatments, and so much more.
This tutorial extensively covers the definitions, nuances, challenges, and requirements for the design of interpretable and explainable machine learning models and systems in healthcare. We discuss many uses in which interpretable machine learning models are needed in healthcare and how they should be deployed. Additionally, we explore the landscape of recent advances to address the challenges model interpretability in healthcare and also describe how one would go about choosing the right interpretable machine learnig algorithm for a given problem in healthcare.
AI in Healthcare | Future of Smart Hospitals Renee Yao
In this talk, I specifically talk about how NVIDIA healthcare AI software and hardware were used to support healthcare AI startups' innovation. Three startups featured: Caption Health, Artisight, and Hyperfine. Audience: healthcare systems CXOs.
Disease prediction and doctor recommendation systemsabafarheen
This paper will tell you how the system will work in terms of disease prediction also will suggest you nearest hospital with experienced doctors, cheap fees
* "Responsible AI Leadership: A Global Summit on Generative AI"
*April 2023 guide for experts and policymakers
* Developing and governing generative AI systems
* + 100 thought leaders and practitioners participated
* Recommendations for responsible development, open innovation & social progress
* 30 action-oriented recommendations aim
* Navigate AI complexities
A short powerpoint presentation on Artificial Intelligence in healthcare settings. This presentation was delivered as a seminar in Department of Community Medicine, RIMS, Imphal, Manipur, India. It was the first seminar on the topic of artificial intelligence, and the topic was covered especially in relation to public health and ethical guidelines.
Artificial intelligence enters the medical fieldRuchi Jain
In the medical and health field, artificial intelligence can help reduce the cost of ongoing health operations, and can have an impact on the quality of medical care for patients everywhere. By diagnosing diseases earlier, AI can also improve patient outcomes. No matter how you look at it, artificial intelligence has great potential in healthcare.
10 Common Applications of Artificial Intelligence in HealthcareTechtic Solutions
List of 10 Common Applications of Artificial Intelligence that explain how artificial intelligence is used in healthcare and why it is necessary? To read briefly all common applications of artificial intelligence in healthcare then visit at https://www.techtic.com/blog/applications-of-ai-in-healthcare/
AI and ML Series - Introduction to Generative AI and LLMs - Session 1DianaGray10
Session 1
👉This first session will cover an introduction to Generative AI & harnessing the power of large language models. The following topics will be discussed:
Introduction to Generative AI & harnessing the power of large language models.
What’s generative AI & what’s LLM.
How are we using it in our document understanding & communication mining models?
How to develop a trustworthy and unbiased AI model using LLM & GenAI.
Personal Intelligent Assistant
Speakers:
📌George Roth - AI Evangelist at UiPath
📌Sharon Palawandram - Senior Machine Learning Consultant @ Ashling Partners & UiPath MVP
📌Russel Alfeche - Technology Leader RPA @qBotica & UiPath MVP
Algorithmic Bias: Challenges and Opportunities for AI in HealthcareGregory Nelson
Gregory S. Nelson, VP, Analytics and Strategy – Vidant Health | Adjunct Faculty Duke University
The promise of AI is quickly becoming a reality for a number of industries including healthcare. For example, we have seen early successes in the augmenting clinical intelligence for diagnostic imaging and in early detection of pneumonia and sepsis. But what happens when the algorithms are biased? In this presentation, we will outline a framework for AI governance and discuss ways in which we can address algorithmic bias in machine learning.
Objective 1: Illustrate the issues of bias in AI through examples specific to healthcare.
Objective 2: Summarize the growing body of work in the legal, regulatory, and ethical oversight of AI models and the implications for healthcare.
Objective 3: Outline steps that we can take to establish an AI governance strategy for our organizations.
When it comes to AI use for prediction, diagnosis and treatment of medical conditions, reality is often replaced with a hype. Limitations should be known. A review of AI failures and challenges in healthcare showing why it is not likely for algorithms to replace physicians in the nearest future.
AI in Healthcare: From Hype to Impact (updated)Mei Chen, PhD
The primary goal of this workshop is to help health professionals gain a critical understanding of the various types of AI technologies available so they can make wise decisions and invest AI for healthcare improvement.
From traffic routing to self-driving cars, Alexa to Siri, AI’s reach is extending into all areas of life, including healthcare. Join Kimberley to learn more about how AI is being used now, and will be used in the near future, to facilitate provider-patient communication, mine medical records, assess patients, predict illness, suggest treatments, and so much more.
This tutorial extensively covers the definitions, nuances, challenges, and requirements for the design of interpretable and explainable machine learning models and systems in healthcare. We discuss many uses in which interpretable machine learning models are needed in healthcare and how they should be deployed. Additionally, we explore the landscape of recent advances to address the challenges model interpretability in healthcare and also describe how one would go about choosing the right interpretable machine learnig algorithm for a given problem in healthcare.
AI in Healthcare | Future of Smart Hospitals Renee Yao
In this talk, I specifically talk about how NVIDIA healthcare AI software and hardware were used to support healthcare AI startups' innovation. Three startups featured: Caption Health, Artisight, and Hyperfine. Audience: healthcare systems CXOs.
Disease prediction and doctor recommendation systemsabafarheen
This paper will tell you how the system will work in terms of disease prediction also will suggest you nearest hospital with experienced doctors, cheap fees
* "Responsible AI Leadership: A Global Summit on Generative AI"
*April 2023 guide for experts and policymakers
* Developing and governing generative AI systems
* + 100 thought leaders and practitioners participated
* Recommendations for responsible development, open innovation & social progress
* 30 action-oriented recommendations aim
* Navigate AI complexities
A short powerpoint presentation on Artificial Intelligence in healthcare settings. This presentation was delivered as a seminar in Department of Community Medicine, RIMS, Imphal, Manipur, India. It was the first seminar on the topic of artificial intelligence, and the topic was covered especially in relation to public health and ethical guidelines.
This workshop is a comprehensive introduction to the application of Generative AI in healthcare. It provides healthcare professionals, educators, and researchers with practical experience in using Generative AI for data analysis, predictive modeling, and personalized treatment planning. The workshop also explores the use of Generative AI in medical education and research. No prior AI experience is required, making this a unique opportunity to learn about the latest advancements in Generative AI and its healthcare applications.
AI in Healthcare APU Using AI in Healthcare for clinical Application research...Vaikunthan Rajaratnam
Discover how generative AI is transforming the face of healthcare. From accelerating drug discovery to empowering personalized treatment, this technology is reshaping the way we deliver and experience care."
Ethical considerations in Generative AI are vital for integrity. Human accountability is emphasized, and interdisciplinary panels are suggested to assess biases comprehensively. Thorough documentation of Generative AI models is urged, promoting transparency with open models. Non-related research applications with generative AI are flagged as high-risk, demanding attention to ethics and integrity. Criteria are proposed to distinguish low and high integrity risks, necessitating tailored mitigation actions. Researchers must report countermeasures, and agreements on acceptable AI models are sought to align with scientific values, excluding outdated or biased models.
Generative AI in Health Care a scoping review and a persoanl experience.Vaikunthan Rajaratnam
A scoping review of the literature, its impact and challenges in healthcare, and a personal experience of its application in practice, teaching, and research.
Artificial Intelligence (AI) has ushered in a transformative era across diverse fields, with its impact being particularly pronounced in the realm of Science, Technology, Engineering, and Mathematics (STEM). In STEM disciplines, AI is proving to be a catalyst for innovation, enabling breakthroughs that were once considered the realm of science fiction.
In research, AI is revolutionizing data analysis. Its ability to swiftly process colossal datasets helps researchers uncover patterns and insights that might have otherwise remained hidden. In fields like genomics, AI algorithms are deciphering the complexities of DNA sequences, accelerating drug discovery and personalized medicine. Moreover, AI-driven simulations are advancing fields like physics and chemistry, enabling virtual experiments that save time, resources, and even offer insights not feasible through traditional methods.
Education in STEM is also undergoing a metamorphosis thanks to AI. Adaptive learning platforms harness AI to tailor educational content to individual student needs, enhancing comprehension and retention. Additionally, AI-driven tools are simplifying complex concepts, making STEM education more accessible to diverse learners.
AI's role in engineering is unparalleled. It facilitates design optimization, aiding engineers in crafting products with superior efficiency and performance. Automation, made possible by AI, streamlines manufacturing processes, increasing precision and reducing errors. Furthermore, AI-infused robotics are venturing into hazardous environments, aiding in tasks that are perilous for humans.
Nonetheless, challenges loom. Ethical concerns regarding bias in AI algorithms must be addressed, particularly when AI influences decisions in STEM, such as medical diagnoses. Striking the right balance between human expertise and AI assistance is crucial to maintaining the integrity of STEM disciplines.
AI's integration into STEM is reshaping research, education, and engineering landscapes. While challenges exist, the potential benefits are undeniable. As AI continues to evolve, its partnership with STEM holds the promise of driving innovation, propelling discoveries, and ultimately shaping a more technologically advanced future.
Innovating Medical-Education with AI Final-2.pptxsbattle
Innovating Medical Education using AI, Agents, LLMs, and deep learning. The benefits and dangers of AI are explored. Popular tools for faculty presented. The possibilities of new faculty/student interaction using Precision Education are offered. Various video excerpts from important innovators is embedded.
Delivering on Responsible AI in HealthcareGregory Nelson
Presented at the ONC Artificial Intelligence Showcase – Seizing the Opportunities and Managing the Risks of Use of AI in Health IT
JANUARY 14, 2022 FROM 12:00 PM TO 4:30 PM ET
https://www.healthit.gov/news/events/onc-artificial-intelligence-showcase-seizing-opportunities-and-managing-risks-use-ai
The Why And How Of Machine Learning And AI: An Implementation Guide For Healt...Health Catalyst
Join Kenneth Kleinberg, Health IT Strategist, and Eric Just, Senior Vice President, Health Catalyst, as they discuss the What, Why, and How of Machine Learning and AI for healthcare leaders.
Attendees will learn:
Practical steps, timeframes and skills as well as real-time data and moving targets associated with the Implementation of ML and AI
How to deal with challenges inherent in ML and AI implementation
What the future holds for ML and AI
_How AI is Transforming the Educational Technology Industry.pdfTechuz
Artificial Intelligence (AI) is revolutionizing the educational technology industry, creating dynamic, personalized learning experiences. At the forefront of this transformation, Techuz leverages AI to develop innovative web development solutions tailored for educational platforms. These AI-driven tools enable adaptive learning, real-time feedback, and data-driven insights, enhancing both teaching and learning processes. With AI, educational institutions can offer customized curricula, automate administrative tasks, and foster engaging, interactive environments for students. As AI continues to evolve, Techuz remains committed to integrating cutting-edge web development practices to shape the future of education, making learning more accessible and effective for everyone.
In February of 2019, the Policy Lab (of the Digital Government Policy and Innovation branch) reported on the work they've been doing towards finalising an AI Ethics framework.
An introduction to the ethics of AI in educationJisc
Presentation slides from Jisc's "an introduction to the ethics of AI in education" event held on 7 December 2021.
This presentation aims:
- To introduce the ethical issues associated with using AI in education
- To explain how ethical issues can be avoided, managed, mitigated and/or overcome
- To introduce you to the Ethical Framework for AI in Education and the Pathway to Ethical AI
Protecting Academic Integrity in the Age of Artificial Intelligence - Keynote...Thomas Lancaster
How should universities think about assessment and academic integrity in light of generative artificial intelligence. These slides from a keynote presentation continue a theme of recent ideas I've explored and also consider how tools like ChatGPT can enable students to succeed.
The Skynet Effect: How HR Can Best Utilize AIAggregage
https://www.humanresourcestoday.com/frs/24235077/the-skynet-effect--how-hr-can-best-utilize-ai/email
AI this, AI that. No matter where you go, AI seems to be all anyone in HR wants to talk about. It might be a little irritating, but it’s inescapable for a good reason. Artificial intelligence, specifically ChatGPT, is now an important topic of conversation for all industries.
Like anything new, there are plenty of questions and misconceptions about how AI will change workplace dynamics. But modern AI isn’t Skynet trying to take over the world, and instead of fearing it, your organization can embrace the efficiencies and positive impacts that it offers.
In this webinar, Iveta Brigis, Vice President, People Operations, and Wesley Pasfield, Head of Data Science will address:
• How to better understand AI, specifically ChatGPT
• Use cases for AI in the employer space
• Considerations and questions to ask when evaluating an AI vendor
• Concerns about AI affecting HR employment availability
• How AI can enhance HR jobs when used responsibly
Discover why nurturing AI in its early stages is crucial for its development. Uncover the secrets to unlocking its potential.
The Need To Nurture AI In Its Infancy
Artificial Intelligence (AI) is a rapidly evolving field with immense potential to transform various industries and revolutionize the way we live and work. As we witness the early stages of AI development, it becomes crucial to recognize the need to nurture this technology in its infancy. Investing in AI research and development is essential to unlock its full potential and reap the benefits it offers. By enhancing AI capabilities through training and data, we can ensure its effectiveness in solving complex problems and making informed decisions. However, alongside these advancements, it is equally important to address the ethical considerations surrounding AI development. Collaborative efforts among researchers, policymakers, and industry leaders are necessary to overcome challenges and shape AI technologies responsibly. By nurturing AI in its infancy, we can pave the way for a future where AI improves our lives while upholding ethical standards and human values.
http://Parenting-an-AI.com
COMPARATIVE ANALYSIS OF CHATGPT-4 AND CO-PILOT IN CLINICAL EDUCATION: INSIGHT...Vaikunthan Rajaratnam
This research investigates the potential of two advanced AI language models, ChatGPT-4 and Co-Pilot, to transform medical education through clinical scenario generation. Focusing on scenarios for Diabetic Neuropathy, Acute Myocardial Infarction, and Pediatric Asthma, the study compares the accuracy, depth, and practical teaching utility of content generated by each platform. A panel of medical experts assessed the AI-generated scenarios, and healthcare professionals provided feedback on their perceived usefulness in educational settings. Results suggest that ChatGPT-4 excels in providing structured foundational knowledge, while Co-Pilot offers greater depth through realistic patient narratives and a focus on holistic care. This indicates that both platforms have value, with their suitability depending on specific educational objectives – ChatGPT-4 aligns better with introductory learning, and Co-Pilot better serves advanced applications emphasizing practical clinical reasoning.
A one day workshop on the use of AI in Healthcare for practice, teaching and research.
The Resource Material for the "AI in Healthcare" workshop serves as an essential guide for healthcare professionals who aim to harness the transformative power of Artificial Intelligence (AI) in clinical practice, medical education, and research. Developed under the expertise of Dr Vaikunthan Rajaratnam, this comprehensive package is designed to complement the workshop, providing both foundational knowledge and practical tools for immediate application.
The slide deck for the "AI for Learning Design" workshop, hosted at Asia Pacific University, serves as a comprehensive guide to integrating Artificial Intelligence into educational settings. Designed to empower educators and instructional designers, the presentation offers actionable strategies for curriculum integration, insights into personalized learning through AI, and a deep dive into the ethical considerations that accompany AI adoption in education. The deck is structured to facilitate an interactive and engaging workshop experience, featuring real-world examples, hands-on activities, and spaces for thought-provoking discussions. Don't miss this invaluable resource for transforming your teaching practices and enhancing educational impact through AI.
empowereing practice in healthcare with generative AI. How to use vairous AI tools to enhance and empowere healthc are practice inlcuidng teaching and research
Academic writing is the backbone of scholarly communication and is vital in knowledge dissemination. However, it can often be challenging and time-consuming, requiring meticulous attention to detail and adherence to established conventions. This is where AI comes into play, offering innovative solutions to streamline and enhance the writing process.
Strategies to reduce post op pain in amputation. Candidates for limb amputation
Risk of developing post-operative pain and phantom limb pain.
Willing and able to participate in post-operative rehabilitation and physical therapy.
Informed consent for the procedure and understand the potential risks and benefits.
Adequate muscle function to allow for TMR surgery to be performed.
Suitable for TMR surgery as per a surgeon's assessment.
Validated tools for assessment of medical disability
At the end of this lecture you will be able to:-
Describe the impact of disease/injury on an individual
List the requirements of an instrument to measure disability
Describe the features of the WHOIDAS 2.0 instrument and its role in medical disability assessment
Assessing medical disability for compensation. The future is based on the changes in Technology, Economy and Socio-Political changes. At the end of this lecture you should be able to:-
Describe the dynamic nature of disability and its impact on an individual
List the factors influencing the assessment of disability
Describe the technological, political and socio-economic influence on medical disability assessment
A new model and tool for surgical skill development to level of mastery.pdfVaikunthan Rajaratnam
A model incorporating motor imagery and mental practice to develop resources for developing surgical skills to a level of mastery. A tool is discussed that guides through developing the instructional material.
Overview Lecture for Occupational Therapists Aug 2022 . At the end of the lecture you should be able to:
Describe the common injuries of the extensor mechanism
Describe the various chronic pathological processes of extensor tendons
List and describe the patho-anatomical basis for their clinical presentation and their complications
Assess, diagnose and describe the principles of management of them
Plan and prescribe a rehabilitation program for the conditions
Medical Technology Tackles New Health Care Demand - Research Report - March 2...pchutichetpong
M Capital Group (“MCG”) predicts that with, against, despite, and even without the global pandemic, the medical technology (MedTech) industry shows signs of continuous healthy growth, driven by smaller, faster, and cheaper devices, growing demand for home-based applications, technological innovation, strategic acquisitions, investments, and SPAC listings. MCG predicts that this should reflects itself in annual growth of over 6%, well beyond 2028.
According to Chris Mouchabhani, Managing Partner at M Capital Group, “Despite all economic scenarios that one may consider, beyond overall economic shocks, medical technology should remain one of the most promising and robust sectors over the short to medium term and well beyond 2028.”
There is a movement towards home-based care for the elderly, next generation scanning and MRI devices, wearable technology, artificial intelligence incorporation, and online connectivity. Experts also see a focus on predictive, preventive, personalized, participatory, and precision medicine, with rising levels of integration of home care and technological innovation.
The average cost of treatment has been rising across the board, creating additional financial burdens to governments, healthcare providers and insurance companies. According to MCG, cost-per-inpatient-stay in the United States alone rose on average annually by over 13% between 2014 to 2021, leading MedTech to focus research efforts on optimized medical equipment at lower price points, whilst emphasizing portability and ease of use. Namely, 46% of the 1,008 medical technology companies in the 2021 MedTech Innovator (“MTI”) database are focusing on prevention, wellness, detection, or diagnosis, signaling a clear push for preventive care to also tackle costs.
In addition, there has also been a lasting impact on consumer and medical demand for home care, supported by the pandemic. Lockdowns, closure of care facilities, and healthcare systems subjected to capacity pressure, accelerated demand away from traditional inpatient care. Now, outpatient care solutions are driving industry production, with nearly 70% of recent diagnostics start-up companies producing products in areas such as ambulatory clinics, at-home care, and self-administered diagnostics.
Global launch of the Healthy Ageing and Prevention Index 2nd wave – alongside...ILC- UK
The Healthy Ageing and Prevention Index is an online tool created by ILC that ranks countries on six metrics including, life span, health span, work span, income, environmental performance, and happiness. The Index helps us understand how well countries have adapted to longevity and inform decision makers on what must be done to maximise the economic benefits that comes with living well for longer.
Alongside the 77th World Health Assembly in Geneva on 28 May 2024, we launched the second version of our Index, allowing us to track progress and give new insights into what needs to be done to keep populations healthier for longer.
The speakers included:
Professor Orazio Schillaci, Minister of Health, Italy
Dr Hans Groth, Chairman of the Board, World Demographic & Ageing Forum
Professor Ilona Kickbusch, Founder and Chair, Global Health Centre, Geneva Graduate Institute and co-chair, World Health Summit Council
Dr Natasha Azzopardi Muscat, Director, Country Health Policies and Systems Division, World Health Organisation EURO
Dr Marta Lomazzi, Executive Manager, World Federation of Public Health Associations
Dr Shyam Bishen, Head, Centre for Health and Healthcare and Member of the Executive Committee, World Economic Forum
Dr Karin Tegmark Wisell, Director General, Public Health Agency of Sweden
Defecation
Normal defecation begins with movement in the left colon, moving stool toward the anus. When stool reaches the rectum, the distention causes relaxation of the internal sphincter and an awareness of the need to defecate. At the time of defecation, the external sphincter relaxes, and abdominal muscles contract, increasing intrarectal pressure and forcing the stool out
The Valsalva maneuver exerts pressure to expel faeces through a voluntary contraction of the abdominal muscles while maintaining forced expiration against a closed airway. Patients with cardiovascular disease, glaucoma, increased intracranial pressure, or a new surgical wound are at greater risk for cardiac dysrhythmias and elevated blood pressure with the Valsalva maneuver and need to avoid straining to pass the stool.
Normal defecation is painless, resulting in passage of soft, formed stool
CONSTIPATION
Constipation is a symptom, not a disease. Improper diet, reduced fluid intake, lack of exercise, and certain medications can cause constipation. For example, patients receiving opiates for pain after surgery often require a stool softener or laxative to prevent constipation. The signs of constipation include infrequent bowel movements (less than every 3 days), difficulty passing stools, excessive straining, inability to defecate at will, and hard feaces
IMPACTION
Fecal impaction results from unrelieved constipation. It is a collection of hardened feces wedged in the rectum that a person cannot expel. In cases of severe impaction the mass extends up into the sigmoid colon.
DIARRHEA
Diarrhea is an increase in the number of stools and the passage of liquid, unformed feces. It is associated with disorders affecting digestion, absorption, and secretion in the GI tract. Intestinal contents pass through the small and large intestine too quickly to allow for the usual absorption of fluid and nutrients. Irritation within the colon results in increased mucus secretion. As a result, feces become watery, and the patient is unable to control the urge to defecate. Normally an anal bag is safe and effective in long-term treatment of patients with fecal incontinence at home, in hospice, or in the hospital. Fecal incontinence is expensive and a potentially dangerous condition in terms of contamination and risk of skin ulceration
HEMORRHOIDS
Hemorrhoids are dilated, engorged veins in the lining of the rectum. They are either external or internal.
FLATULENCE
As gas accumulates in the lumen of the intestines, the bowel wall stretches and distends (flatulence). It is a common cause of abdominal fullness, pain, and cramping. Normally intestinal gas escapes through the mouth (belching) or the anus (passing of flatus)
FECAL INCONTINENCE
Fecal incontinence is the inability to control passage of feces and gas from the anus. Incontinence harms a patient’s body image
PREPARATION AND GIVING OF LAXATIVESACCORDING TO POTTER AND PERRY,
An enema is the instillation of a solution into the rectum and sig
Leading the Way in Nephrology: Dr. David Greene's Work with Stem Cells for Ki...Dr. David Greene Arizona
As we watch Dr. Greene's continued efforts and research in Arizona, it's clear that stem cell therapy holds a promising key to unlocking new doors in the treatment of kidney disease. With each study and trial, we step closer to a world where kidney disease is no longer a life sentence but a treatable condition, thanks to pioneers like Dr. David Greene.
One of the most developed cities of India, the city of Chennai is the capital of Tamilnadu and many people from different parts of India come here to earn their bread and butter. Being a metropolitan, the city is filled with towering building and beaches but the sad part as with almost every Indian city
Explore our infographic on 'Essential Metrics for Palliative Care Management' which highlights key performance indicators crucial for enhancing the quality and efficiency of palliative care services.
This visual guide breaks down important metrics across four categories: Patient-Centered Metrics, Care Efficiency Metrics, Quality of Life Metrics, and Staff Metrics. Each section is designed to help healthcare professionals monitor and improve care delivery for patients facing serious illnesses. Understand how to implement these metrics in your palliative care practices for better outcomes and higher satisfaction levels.
R3 Stem Cells and Kidney Repair A New Horizon in Nephrology.pptxR3 Stem Cell
R3 Stem Cells and Kidney Repair: A New Horizon in Nephrology" explores groundbreaking advancements in the use of R3 stem cells for kidney disease treatment. This insightful piece delves into the potential of these cells to regenerate damaged kidney tissue, offering new hope for patients and reshaping the future of nephrology.
The dimensions of healthcare quality refer to various attributes or aspects that define the standard of healthcare services. These dimensions are used to evaluate, measure, and improve the quality of care provided to patients. A comprehensive understanding of these dimensions ensures that healthcare systems can address various aspects of patient care effectively and holistically. Dimensions of Healthcare Quality and Performance of care include the following; Appropriateness, Availability, Competence, Continuity, Effectiveness, Efficiency, Efficacy, Prevention, Respect and Care, Safety as well as Timeliness.
CHAPTER 1 SEMESTER V PREVENTIVE-PEDIATRICS.pdfSachin Sharma
This content provides an overview of preventive pediatrics. It defines preventive pediatrics as preventing disease and promoting children's physical, mental, and social well-being to achieve positive health. It discusses antenatal, postnatal, and social preventive pediatrics. It also covers various child health programs like immunization, breastfeeding, ICDS, and the roles of organizations like WHO, UNICEF, and nurses in preventive pediatrics.
1. AI in Healthcare
Vaikunthan Rajaratnam
Senior Consultant Hand Surgeon, KTPH, Singapore,
Adjunct Professor & UNESCO Chair Partner,
Asia Pacific University of Technology and Innovation, Malaysia.
25 November 2023
2. Warning:
Unprecedented Levels of Productivity
and Inspiration Ahead!
Please be advised:
The content of this workshop is so intensely
engaging and empowering in the realm of AI in
healthcare that it carries a high risk of sparking a
newfound addiction to productivity and innovation.
Attendees may experience an irresistible urge to
apply transformative skills and insights in their
professional practice, leading to significant
advancements in healthcare. Proceed with
enthusiasm and caution – you're stepping into a
world of exhilarating empowerment!
Embrace the journey, but don't say we didn't
warn you!
3. Disclaimer
• I am not an AI expert, nor do I possess coding knowledge specific to the underlying mechanisms of AI models;
• My expertise lies in the utilisation of these models, such as ChatGPT, based on my extensive experience as a
user within the fields of healthcare, medical education, and related research, rather than their technical
development or underlying algorithms.
• This workshop is intended solely for educational and informational purposes in AI and healthcare.
• The views expressed herein are my own, borne from extensive experience in surgery, medical education, and
instructional design, and do not necessarily reflect those of any associated institutions.
• While I endeavour to provide accurate and up-to-date information, no guarantee is given regarding its applicability.
• Participants acknowledge and assume responsibility for using the information provided by engaging in this
workshop.
Vaikunthan Rajaratnam
6. Framework for the Integration of Generative AI Skills into the
Teaching and Learning Practice
Domains
Foundational Knowledge of
AI and Generative AI
Pedagogical
Integration
Technical Proficiency
Ethical and Responsible
Use
Assessment and Evaluation
Professional Development
and Lifelong Learnin
Community and
Stakeholder Engagement
Rubrics
Understanding AI Concepts,
Fundamentals of Generative AI
Descriptors
Grasp of basic AI terminologies and principles; Demonstrates the
capabilities and limitations of generative models.
Curricular Mapping, Instructional
Design
Demonstrates the ability to align Generative AI tools with
curricular goals; Proficiency in integrating Generative AI in lesson
designs.
Tool Management, Data Literacy Skill in selecting and operating Generative AI platforms;
Demonstrates the ability to interpret and analyse data.
Data Privacy, Ethical Considerations Demonstrate the incorporation and compliance with data
protection laws in the practice; and the ethical implications,
including biases.
Formative Assessment, Summative
Evaluation
Demonstrate the capability to employ Generative AI for real-time
assessments; Integrate using AI data for evaluations.
Self-updating, Peer Training Demonstrate commitment to staying updated with AI
advancements; Willingness to train and mentor peers..
Communication, Collaboration Demonstrate the ability to articulate the role of Generative AI to
stakeholders; Actively seeking partnerships with experts.
7. Section Ethical Principles or Elements Description
Beneficence and Non-
Maleficence
Holistic Well-being Beyond intellectual growth, AI should contribute to emotional and social well-being.
Cultural Relevance Educational content should respect and incorporate local traditions, beliefs, and moral
systems.
Autonomy Informed Participation Users should be fully informed about how AI will be used.
Agency Family and community should also be involved in decision-making processes regarding
AI adoption in education.
Social Justice Equitable Access Special focus on providing equal access to quality education across various societal
strata.
Bias Mitigation Efforts must be made to eliminate biases related to gender, social class, or ethnicity.
ASIAN Values Harmony AI should aim for social harmony and integrate well with existing educational systems.
Respect for Authority AI should not undermine the teacher's role but should enhance the traditional teacher-
student relationship.
Stakeholder Collaboration Government Agencies Develop and enforce regulations and guidelines.
Educational Institutions Implement and adhere to ethical guidelines.
AI Developers Ensure the ethical design and deployment of AI.
Ethicists and Philosophers Continually review and update ethical guidelines.
Community and Family Participate in decision-making processes.
Evaluation and Monitoring Regular Audits Conduct regular ethical audits to ensure that AI tools comply with the framework.
Feedback Loops Create mechanisms for students, educators, and families to provide feedback on AI
ethical considerations.
8. PRODUCTS
• Tools for Effective Academic Courses and Holistic Teaching
•MOE Malaysia
AI TEACH
• Learning Designs
•APU, Malaysia, NHG, Singapore
AI LD
• Health Professional
•Perdana University , Malaysia, BDSSH, Bangladesh
•NHG, Singapore, Sengkang, Singapore
AI HP
• Research
•Perdana University, Malaysia, Sengkang , Singapore
•University of Eswatini (Africa)
AI RE
•Academic Writing
•APU, Perdana University, Malaysia
•University of Eswatini (Africa)
AI AW
• Leveraging Efficiency in Administrative Proficiency
•MOE, Dubai
AI LEAP
9.
10. Introduction to AI in
Healthcare:
Opportunities and
Challenges
AI technologies have the potential to
revolutionise healthcare by enhancing
diagnosis, treatment planning, and research.
AI won't replace you, but someone
empowered by AI undoubtedly will
11.
12. Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of artificial intelligence in healthcare: A structured
literature review. BMC Medical Informatics and Decision Making, 21(1), 125. https://doi.org/10.1186/s12911-021-01488-9
14. Predictiv
e
medicine
Early Disease Detection
Personalized Treatment Plans
Chronic Disease Management
Genomic Medicine and Genetic Risk Prediction
Drug Response Prediction
Epidemic Outbreak Prediction
Hospital Readmission Prediction
17. Challenges
Golhar, S. P., & Kekapure, S. S. (2022). Artificial Intelligence in Healthcare—A Review. International Journal of Scientific
Research in Science and Technology, 9(4), 381–387. https://doi.org/10.32628/IJSRST229454
18. Governance
Model for AI
S. Reddy, S. Allan, S. Coghlan, and P. Cooper, ‘A governance model for the application of AI in health care’, J. Am. Med. Inform. Assoc., vol. 27, no.
3, pp. 491–497, Mar. 2020, doi: 10.1093/jamia/ocz192
Rahman, N., Thamotharampillai, T., & Rajaratnam, V. (2023). Ethics, guidelines, and policy for technology in healthcare. In
Medical Equipment Engineering: Design, Manufacture and Applications (pp. 119–147). IET Digital Library.
https://doi.org/10.1049/PBHE054E_ch9
19. Higgins, D., & Madai, V. I. (2020). From Bit to
Bedside: A Practical Framework for Artificial
Intelligence Product Development in
Healthcare. Advanced Intelligent Systems,
2(10), 2000052.
https://doi.org/10.1002/aisy.202000052
20. EPIC and AI
Abridge's Clinical
Documentation
Tool Integration:
• Creates near-instant
visit summaries.
Generative AI for
Patient Messaging
by Ochsner Health:
• Generative AI to draft
messages to patients.
Partnership with
Microsoft
• Integrate large
language models
Emory Healthcare's
Collaboration with
Abridge:
• Ambient listening
solution for note-taking
during doctor's
appointments.
21. Personalised chatbots & Epic EHR system
• Interprets caller intent and provides
immediate, personalised assistance
Avaamo's AI-Powered
Patient Experience:
• Automates patient communications.
Asparia's Chatbot
Integration:
• Extract and analyse patient data &
generates detailed medical reports
Epic-Chatbot Using
ChatGPT
22. Artificial
Intelligence
Enables machines
to mimic human
intelligence and
perform tasks that
typically require
human intelligence
• Machines learn from data
• recognize patterns
• make decisions, and
• solve problems without explicit
programming
• Algorithms and statistical models
• analyse large amounts of data
• generate insights and predictions.
• Narrow AI
• designed for specific tasks like image
recognition or natural language
processing, and
• General AI
• aims to possess human-like intelligence
across a wide range of tasks.
24. What is Generative AI?
• Understanding Language
• Reads and comprehends human-written text.
• Generating Text
• Writes human-like text, from answers to creative content.
• Conversation
• Capable of engaging in text-based conversations with users.
• Applications
• Used in virtual assistants, education, content creation, and
more.
• Not a Human
• Generates text through algorithms, without feelings or
consciousness.
AI for Clinical Decision-Making and Patient Care
25. AI & Generative AI
• AI (Artificial Intelligence)
• refers to the simulation of human intelligence in
machines that are programmed to think, learn, and
make decisions
• Applications: Includes machine learning, natural
language processing, robotics, computer vision, etc.
• Generative AI
• subset of AI that focuses on creating new data
instances that are similar to a set of training
examples.
• Techniques: Examples include Generative Adversarial
Networks (GANs), Variational Autoencoders (VAEs),
etc.
• ChatGPT (Generative Pretrained Transformer):
• State-of-the-art language models developed by
OpenAI. It utilises the Transformer architecture to
generate human-like text based on given prompts.
• Usage: Widely used in natural language understanding
tasks, chatbots, content creation, and more.
• Bing CoPilot
• Bard
• Claude 2
26. How Does Generative AI Work?
Don’t cry ………..”
“ Don’t cry over….”
• Reading Text
• Takes in words, questions, or
sentences as input
• Understands the language like a
human reading a book
• Processing Information
• Breaks down the input into
smaller parts to understand the
meaning.
• Uses a complex mathematical
model to analyse the text.
• Generating Response
• Constructs a response based on
what it has "learned" from
reading lots of text.
• Tries to make the response sound
like something a human would
say.
• No Personal Knowledge or Opinions
• Doesn't have thoughts, feelings,
or personal experiences.
• Answers are based on patterns in
the data it was trained on, not
personal beliefs or opinions.
• Learning from Data
• Trained on vast text from
books, websites, and other
written materials.
• Learns language structure
and how to create sentences
that make sense.
• Versatility
• Can be used for tasks like
answering questions, writing
stories, or helping
with homework.
• Adaptable to different
subjects and contexts.
• Not Perfect
• Can make mistakes or provide
incorrect information.
• Needs to be used with
caution, especially for critical
or sensitive topics
28. Understanding Generative AI
• Advanced language
model developed by
OpenAI.
• Generates human-like
text based on the
prompts.
• Quality vs prompt.
Quality of Response ∝ Quality of Prompt × Model Understanding
Here:
Quality of Response is the measure of how relevant, accurate, and coherent the response is.
Quality of Prompt represents the clarity, specificity, and relevance of the prompt given to the model.
Model Understanding , model's ability to interpret the prompt, including its training, design, and current context.
30. Tool: Prompting
"prompting" refers to the input or
question that you provide to the
model. The model takes this prompt
and generates a response based on
the information it has been trained
on.
• Initial Statement or Question
• Context
• Intended Output
• Tone or Formality
• Specificity
• Instructions for Response Format
31. Prompt Generation
• Define the Objective:
• Identify the specific information or assistance
• Be Clear and Precise:
• Use clear language and avoid ambiguity.
• Include essential details without over-
complicating the prompt.
• Consider Context:
• Provide relevant background or context to
guide the response.
• Set the Tone and Style:
• Specify the desired tone (formal, casual) or
style (e.g., summary, explanation) if it matters
for your use case.
• Ask Direct Questions:
• If seeking specific information, formulate your
prompt as a direct question.
• Self-Reflective
• Avoid Bias and Leading Questions:
• Craft the prompt neutrally to prevent biased
or skewed responses.
• Test and Refine:
• Experiment with different phrasings and
observe how slight changes can affect
the response.
• Refine the prompt
• Consider Ethical and Privacy Concerns:
• Ethical guidelines and does not request or
reveal sensitive or private information.
32. Bad Prompts Comments Good Prompts Comments
Tell me about heart
problems.
Too vague, lacks
focus and context.
Summarize the diagnostic criteria for
Congestive Heart Failure according to
the latest ACC/AHA guidelines.
Specific, focused, and
references a reputable
source.
What drugs are good
for high BP, diabetes,
and heart issues?
Overly complex,
risks dangerous
oversimplification.
List the first-line antihypertensive
medications according to the latest
guidelines.
Focused on a single
condition, asks for
evidence-based
treatment.
What's the best
treatment for a 45-
year-old male named
John Smith with
these symptoms?
Contains potentially
identifiable
information, risking
patient
confidentiality.
What are the treatment options for a
45-year-old male presenting with
these generic symptoms?
Generalized and
anonymized,
preserving patient
confidentiality.
33. Response Validation
• Review response - meets your requirements.
• No access to real-time data
• Vaildate Validate Validate.
• Prompt – response -refine - reprompt.
Relevance Check
Accuracy
Confirmation
Context
Consistency
Sensitivity Review
Refinement for
Future Queries
36. Please respond to the following query with a
structured and academic approach suitable for
a university lecturer.
Include bullet-point answers where applicable,
supported by relevant examples from scholarly
literature.
Ensure that all statements are backed by
credible evidence and provide appropriate
references and citations in accordance with
standard academic citation styles (e.g., APA,
MLA, or Chicago).
The response should be clear, concise, and
tailored to an academic audience engaged in
higher education teaching and research."
Personalizing Gen-AI
37. • Professional Tone & Evidence-Based Approach: Maintain a formal tone and
rely on evidence-based information, aligning with Dr. Rajaratnam's scholarly
background.
• Expertise in Healthcare, Education, and AI: Prepare for in-depth discussions
in these fields, reflecting Dr. Rajaratnam's extensive experience and
contributions.
• Ethical and Global Perspective: Factor in ethical considerations for AI
applications and be sensitive to international norms, given Dr. Rajaratnam's
global collaborations and ethical guidelines.
• Technological and Interdisciplinary Focus: Be ready to introduce tech-based
solutions and consider interdisciplinary approaches, corresponding with his
interests in instructional design and AI.
• Social Impact and Local Context: Prioritize broader social impact and
humanitarian goals, and adapt information to the Singaporean and Malaysian
context, where Dr. Rajaratnam is actively engaged.
38.
39. Generative
AI platforms
Feature ChatGPT Microsoft Copilot
Integration
Available as an API that can
be integrated into different
applications1
Integrated with Microsoft
365 and other services1
Specialization
Designed to mimic human
conversation by
understanding your question
or comment and responding
in an engaging and
conversational way1
AI-powered digital assistant
that aims to provide
personalized assistance to
users for a range of tasks and
activities1
Versatility
Can handle a wide range of
tasks and domains, such as
writing essays, emails,
poems, songs, summaries,
etc1
Combines the power of large
language models (LLMs) with
your data in the Microsoft
Graph (including your
calendar, emails, chats,
documents, meetings, and
more) and the Microsoft 365
apps1
Control
Gives more control to the
user over what they want to
generate1
Works as a digital assistant
that fills in the blanks for the
user1
40.
41.
42. Aspect ChatGPT Response Other Chatbot Response
Non-invasiveness & Practicality Mentioned as a key advantage,
emphasizing suitability for
community settings.
Highlighted as a practical tool for
community screening due to its
rapid, non-invasive nature.
Early Detection Stressed the ability to detect
small fiber damage before clinical
symptoms.
Noted for its use in early
detection, particularly of small
fiber nerves.
Correlation with Neuropathy
Severity
Discussed the correlation
between CCM findings and
neuropathy severity.
Not specifically addressed.
Predictive Value Mentioned its potential in
predicting the development of
diabetic neuropathy.
Focused on predictive validity,
especially for future development
of Diabetic Peripheral
Neuropathy.
Repeatability and Reliability Emphasized the importance of
repeatability and reliability.
Briefly mentioned as repeatable
but didn't elaborate on reliability.
Telemedicine Potential Addressed the potential use in
telemedicine.
Not discussed.
Limitations and Challenges Discussed limitations such as the
need for specialized equipment
and training.
Not discussed.
Detailed Description Provided a detailed, multifaceted
analysis.
More focused on key points, less
detailed in comparison.
43. ChatGPT4 Opinion
• ChatGPT Response: This response is comprehensive,
addressing various aspects, including predictive value,
telemedicine potential, and limitations. It provides a nuanced
understanding of CCM's role in diabetic neuropathy screening,
suitable for an audience seeking an in-depth analysis.
• Co Pilot Response: This response is concise and focused,
highlighting key advantages of CCM, such as its non-
invasiveness and predictive validity. It's more streamlined,
making it suitable for readers looking for a quick overview
without extensive background detail.
ChatGPT offers a detailed, academic-oriented approach, beneficial for in-depth understanding, while the other chatbot provides
a succinct summary, ideal for a general overview. Both have their unique strengths, and the preference would depend on the
depth of information and type of analysis the user requires.
44. Copilot Opinion Copilot Response GPT4 Response
Early Detection
Emphasized the ability of CCM to detect
small fibre damage at an early stage.
Highlighted the importance of early
detection and intervention in diabetes.
Non-Invasive Nature
Mentioned the non-invasive nature of
CCM.
Discussed the non-invasive nature of
CCM and its suitability for community
settings.
Predictive Value
Highlighted the predictive value of CCM
in identifying high-risk individuals.
Discussed the predictive capability of
CCM in identifying high-risk individuals.
Repeatability and
Reliability
Discussed the repeatability and reliability
of CCM for monitoring disease
progression.
Mentioned the repeatability and
reliability of CCM, and its importance for
longitudinal studies and screening
programs.
Correlation with
Neuropathy Severity
-
Mentioned the correlation of CCM
findings with neuropathy severity.
Potential in
Telemedicine
-
Discussed the potential of CCM in
telemedicine.
Limitations and
Challenges
-
Outlined the limitations and challenges
of implementing CCM in community
settings.
Please note that “-” indicates that the topic was not
covered in the respective response.
Both responses provide
a comprehensive
overview of the role of
CCM in diabetic
neuropathy screening.
However, the user’s
response provides a
more detailed
discussion by including
the correlation with
neuropathy severity,
potential in
telemedicine, and the
limitations and
challenges of CCM.
These additional details
offer a more nuanced
understanding of the
practical implications
of using CCM in
community settings
45.
46. Login to your choice of
Generative AI
• Ask a clinical question based on a good
prompt and have three conversations
related to your question.
• Share your responses
• How would you use it in your practice?
• Post to this Padlet
48. Patient Triage:
•Appropriate level of
care
Mental Health
Support:
•Immediate, cost-
effective
Patient
Education:
•Provide reliable and
continuous
information, explain
treatment options, or
clarify post-operative
care instructions.
Remote
Monitoring:
•Ensure medication
adherence, and alert
clinicians about
anomalies.
Clinical Decision
Support:
•Data-driven insights
to support clinical
decisions.
Confidentiality and
Compliance:
Ensure that all interactions are
secure and compliant with
healthcare regulations.
68. Use a clinical situation / administrative problem and
craft prompts for the various AI platforms
and post the response
69. Relevance to healthcare education
• Adapts to individual student needs
Personalized
Learning:
• Creating diverse and engaging educational materials.
Content Creation:
• Interactive learning experiences (Chatbot)
Student Engagement:
• Provides real-time assessment and feedback .
Assessment and
Feedback:
• content accessible to diverse learners
Accessibility:
• Facilitates collaboration among students and educators,
bridging geographical and language barriers.
Collaboration and
Communication:
70. Personalized Learning
• Tailors educational content
Adaptive Content Delivery:
• Provides instant feedback and real-time assistance
Real-Time Feedback and
Support:
• Engages with interactive dialogues and Simulates scenarios.
Interactive Learning
Environments:
• Analyses - identify strengths and weaknesses for personalized learning.
Data-Driven Insights:
• Adapts content to diverse learners & multiple languages.
Accessibility and Inclusivity:
• Facilitates collaborative learning experiences and peer interactions.
Collaboration and Peer
Interaction:
• Seamlessly integrates with Learning Management Systems (LMS)
Integration with Existing
Platforms:
• Supports lifelong learning and Assists in tracking and maintaining
professional development
Continuous Learning and Skill
Development:
• Ensures ethical guidelines and privacy regulations.
Ethical and Privacy
Considerations:
• Aligns personalized learning experiences and Ensures relevance to real-
world medical practice
Alignment with Healthcare
Objectives:
75. 1.Question: Which of the following statements best describes
the role of HbA1c in managing diabetes?
1. A) HbA1c is primarily used to diagnose acute diabetic
complications.
2. B) HbA1c levels reflect the average blood glucose levels
over the past 2-3 months.
3. C) HbA1c is a short-term marker for blood glucose
fluctuation.
4. D) HbA1c measures the immediate postprandial blood
glucose level.
Answer: B) HbA1c levels reflect the average blood glucose
levels over the past 2-3 months.
1.Question: A 54-year-old patient with Type 2 diabetes presents
with an HbA1c of 8.0%. What is the most appropriate initial
approach?
1. A) Immediate hospitalisation for insulin therapy.
2. B) Evaluation and optimisation of the current treatment
regimen.
3. C) Disregarding the HbA1c level as it is within the normal
range.
4. D) Starting an antihypertensive medication
.hospitalisation
78. I have been asked
to create a module
for the
examination of the
abdomen for
organomegaly for
medical students.
Create a
curriculum and
include learning
outcomes and the
pedagogy and a
lesson plan
88. • Be clear & descriptive
• Specific styles or
techniques
• Create a test version
• Evaluate the result
• Refine the prompt
• Iterative process
89. AI for Video Production & Image
generation
Draft
Learning
Outcomes
LO to
Prompt
ChatGPT
for video
script
Import/edi
t script to
AI Video
Generator
Add
personalised
media
Choose
Voiceover
type
Produce
Review
and
Upload
90. Write a script
for the
introduction of
the anatomy of
the
organomegaly
medical student
module. This
will be a 90
second video
script. Just
provide the
narration
98. Generating Lecture
Content
• Participants use
their prompts to
generate an outline
and main content
for a lecture.
Validating AI
Responses
• Participants validate
and refine the AI-
generated content
for their lecture.
Integrating and
Refining Lecture
Content
• Finalizing the
lecture content,
incorporating
validated
information and
personal expertise.
99. Part 1: Scriptwriting
with ChatGPT
• Participants create a
draft script for a
surgical procedure
or topic of their
choice using
ChatGPT.
• Copy script and edit
in word doc.
Part 2: Creating AI-
Generated Art
• Participants
generate AI art
relevant to their
video script.
• Download for use in
video
Part 3: Video
Assembly using
InVideo (40 minutes)
• Overview of InVideo
interface and
features.
• Integrating AI-
generated art and
script into a
cohesive video.
• Using text-to-speech
for narration.
107. Add SciSpace Copilot to your browser
AI research assistant that explains the text, math, and tables in
scientific literature like research papers, technical blog posts, or
reports. You can also ask follow-up questions, and it will give
you instant answers.
114. Title insights Authors Date Journal name
Asian (Bio)Values: Constructing Asian
Difference and Biovalue in the Singapore
Diabetes Discourse
The provided information does not address
the integration of Asian values into western
bioethics frameworks.
Mohammad Khamsya Bin Khidzer 21/6/2023 Science, Technology,
& Human Values
Bioethics Across the Globe: Rebirthing
Bioethics
The paper suggests discussing Bioethics in
Asia" to incorporate Asian values into the
existing framework of bioethics."
Akira Akabayashi 19/5/2020
Beyond a Western Bioethics in Asia and Its
Implication on Autonomy.
The article explores integrating Asian values
into Western bioethics frameworks,
particularly in the areas of breaking bad
news, giving consent, determining best
interests, and end-of-life care.
Mark Tan Kiak Min 8/7/2017
Translating Asian Bioethics into developing
global Biocultures Translational Challenges
In Bioethics
Hans-Martin Sass 22/12/2015 Jahr - European
journal of bioethics
Culture and ethics in medical education: The
Asian perspective.
Muhammad Shahid Shamim, Lubna
Baig, Adrienne Torda, Chinthaka
Balasooriya
1/3/2018 Journal of Pakistan
Medical Association
Bioethics as an Approach to Nanoethics in
China and the EU
Sally Dalton-Brown 1/1/2015
Bioethics in East Asia: Development and
Issues
Myongsei Sohn 1/1/2016
(East) Asia" as a Platform for Debate:
Grouping and Bioethics."
Margaret Sleeboom-Faulkner 1/1/2016 Kennedy Institute of
Ethics Journal
Western or Eastern principles in globalized
bioethics? An Asian perspective view
Michael Cheng-Tek Tai 1/3/2013 Tzu Chi Medical
Journal
Eubios Journal of Asian and International
Bioethics
Yayi Suryo Prabandari, Claire Lajaunie,
Serge Morand, Tan Boon Huan
1/1/2014
125. Practical exercise
• Use Gen AI to help with generating
content, phrasing, or grammar and
style checking as needed. Feel free to
collaborate with your peers, share
ideas, and provide feedback to each
other.
• After completing the draft, share it
with the group if you feel comfortable.
We'll discuss the drafts collectively,
providing constructive feedback and
suggestions for improvement.
• Validate the responses of ChatGPT and
incorporate in writing
• Remember, the introduction is your
chance to grab the reader's attention
and convince them of the importance
of your research, so make it engaging
and informative! (use this in your
prompts when writing the
introduction!)
126. Peer review and
Feed back
• Present your prompts and the
responses
• Show your Literature Table
• Show how you validated the
Generative AI’s response
127. Goals
• Purpose and
components of
methods
• Structure the
methods
• Typeset for methods
review
• Using ChatGPT with
prompts
128. Purpose and Structure of the Methods
Section
Explanation of
the procedures
used
Selection of
Participants
Description of
Procedures
and Materials
Data Collection
Methods
Data Analysis
Methods
Ethical
Considerations
Limitations and
Assumptions
Replicability of
the Study
129. AI Tools for RESEARCH
• Elicit for Literature Search
• Scholarcy and Typeset for data
extraction and summary
• Genei.io for summarisation and
key points highlighting
• Keyword generation with ChatGPT
( targeted prompt engineering)
140. The Art and Science of Qualitative Research
https://tinyurl.com/QUALIRE
Introduction to research in healthcare
https://tinyurl.com/HCARERE
AICHAT BT FOR Research in healthcare
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Editor's Notes
The clinical domain refers to identifying real‐world clinical needs and validating these needs throughout the life cycle of the project. Herein, the major risks, objectives and key results, and practical advice, across the three time‐phases of development, are presented.
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Infographics
Whether the watermills of millennial past, or the today's lecture room mechanics, plentiful evidence points to humanity's long history of creating a paradise to undertake a repetitive work.