1- AI has achieved high sensitivity of 91-94% and specificity of 96-100% in detecting lung cancer from chest radiography images, demonstrating its ability to support medical imaging analysis.
2- While AI will not replace medical professionals, it can serve as a tool to assist clinicians by analyzing large amounts of data, aiding clinical decisions, and improving outcomes. Primary care physicians may use AI for tasks like note-taking and presenting insights into patients' needs.
3- For AI to be implemented responsibly, its development must address issues like privacy, bias, and transparency to avoid harmful consequences and build trust with clinicians and the public. Collaboration between technology developers and civil society can help ensure AI is developed and applied
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/
The use of artificial intelligence in healthcare has the potential to assist healthcare providers in many aspects of patient care and administrative processes as well as improve patient outcomes.
AI analyzes data throughout a healthcare system to mine, automate and predict processes. Some of the use cases are :
1. Early Diagnosis of diseases
2. Improved clinical trial processes
3. Mental health apps etc.
artificial intelligence in health care. how it is different from traditional techniques. growth of artificial intelligence. how hospitals are taping artificial intelligence to mange corona virus. pros and cons of artificial intelligence.
Artificial intelligence in health care by Islam salama " Saimo#BoOm "Dr-Islam Salama
A Lecture about basics and concepts of Artificial Intelligence in health care & there applications
محاضرة عامة حول الذكاء الإصطناعي وأساسياته في الرعاية الصحية والطبية وتطبيقاته
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.
Artificial intelligence (AI) is already transforming healthcare. It's an invaluable tool, capable of storing and processing vast amounts of data almost simultaneously. AI allows for rapid and accurate diagnosis, early detection, advanced research and much more.
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/
The use of artificial intelligence in healthcare has the potential to assist healthcare providers in many aspects of patient care and administrative processes as well as improve patient outcomes.
AI analyzes data throughout a healthcare system to mine, automate and predict processes. Some of the use cases are :
1. Early Diagnosis of diseases
2. Improved clinical trial processes
3. Mental health apps etc.
artificial intelligence in health care. how it is different from traditional techniques. growth of artificial intelligence. how hospitals are taping artificial intelligence to mange corona virus. pros and cons of artificial intelligence.
Artificial intelligence in health care by Islam salama " Saimo#BoOm "Dr-Islam Salama
A Lecture about basics and concepts of Artificial Intelligence in health care & there applications
محاضرة عامة حول الذكاء الإصطناعي وأساسياته في الرعاية الصحية والطبية وتطبيقاته
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.
Artificial intelligence (AI) is already transforming healthcare. It's an invaluable tool, capable of storing and processing vast amounts of data almost simultaneously. AI allows for rapid and accurate diagnosis, early detection, advanced research and much more.
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.
Short overview over possibilities and challenges of using artificial intelligence in health care. Presentation from the MultiHelix ThinkTank, May 14 2020.
Artificial Intelligence In Medical IndustryDataMites
Medical artificial intelligence (AI) mainly uses computer techniques to perform clinical diagnoses and suggest treatments. AI has the capability of detecting meaningful relationships in a data set and has been widely used in many clinical situations to diagnose, treat, and predict the results.
visit : https://datamites.com/artificial-intelligence-course-training-pune/
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.
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.
Artificial Intelligence in Health Care 247 Labs Inc
This presentation was shown at the Artificial Intelligence in Health Care event in Toronto Nov 16 2017. The discussion was to introduce various applications of artificial intelligence and machine learning in the health care field.
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.
Healthcare AI will undoubtedly become one of the fastest growing industries in the industry. Although the medical and health artificial intelligence industry was valued at US$ 600 million in 2014 , it is expected to reach a staggering US$ 150 billion by 2026. There are countless AI applications in the healthcare industry, let’s look at some outstanding ones.
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.
Artificial Intelligence (AI) is shaping and reshaping every industry under the sun. The Healthcare industry is not any exception.
In this presentation, I have discussed the basics of AI as well as how it is being used in various branches of the healthcare industry. I presented this topic in my departmental seminar in October 2021 and received appreciation as well as positive feedback in this regard.
This presentation discuss major applications of AI in Healthcare including medical diagnostics, personalized treatments and optimizing US healthcare system. This presentation also discuss some of the challenges of implementing AI 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.
Short overview over possibilities and challenges of using artificial intelligence in health care. Presentation from the MultiHelix ThinkTank, May 14 2020.
Artificial Intelligence In Medical IndustryDataMites
Medical artificial intelligence (AI) mainly uses computer techniques to perform clinical diagnoses and suggest treatments. AI has the capability of detecting meaningful relationships in a data set and has been widely used in many clinical situations to diagnose, treat, and predict the results.
visit : https://datamites.com/artificial-intelligence-course-training-pune/
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.
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.
Artificial Intelligence in Health Care 247 Labs Inc
This presentation was shown at the Artificial Intelligence in Health Care event in Toronto Nov 16 2017. The discussion was to introduce various applications of artificial intelligence and machine learning in the health care field.
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.
Healthcare AI will undoubtedly become one of the fastest growing industries in the industry. Although the medical and health artificial intelligence industry was valued at US$ 600 million in 2014 , it is expected to reach a staggering US$ 150 billion by 2026. There are countless AI applications in the healthcare industry, let’s look at some outstanding ones.
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.
Artificial Intelligence (AI) is shaping and reshaping every industry under the sun. The Healthcare industry is not any exception.
In this presentation, I have discussed the basics of AI as well as how it is being used in various branches of the healthcare industry. I presented this topic in my departmental seminar in October 2021 and received appreciation as well as positive feedback in this regard.
This presentation discuss major applications of AI in Healthcare including medical diagnostics, personalized treatments and optimizing US healthcare system. This presentation also discuss some of the challenges of implementing AI in healthcare.
Artificial intelligence in field of pharmacyKaustav Dey
AI is a program designed to produce outcome in a manner similar to human intelligence,logic and reasoning.This can be used in field of Pharmacy for betterment of humankind, to save lives,money and time
Artificial Intelligence Service in HealthcareAnkit Jain
It is no secret that artificial intelligence is shaping new business landscapes in every industries. As one of emerging convergence technologies, Artificial Intelligence (AI) creates new products and services, finally innovating business models. Especially, it has been noted by industry experts and researchers that healthcare sector has the biggest potential of AI convergence. In fact, major technology companies including Google, Microsoft and IBM have invested in AI in healthcare sector. Thousands of AI startups are active launching innovative services related to healthcare.
Everything you want to know about role of artificial intelligence in drug discovery.
Artificial intelligence in health care and pharmacy, drug discovery, tensorflow, python,
deep neural network, GANs
AI in drug discovery and development
AI in clinical trials
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
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
Health Education on prevention of hypertensionRadhika kulvi
Hypertension is a chronic condition of concern due to its role in the causation of coronary heart diseases. Hypertension is a worldwide epidemic and important risk factor for coronary artery disease, stroke and renal diseases. Blood pressure is the force exerted by the blood against the walls of the blood vessels and is sufficient to maintain tissue perfusion during activity and rest. Hypertension is sustained elevation of BP. In adults, HTN exists when systolic blood pressure is equal to or greater than 140mmHg or diastolic BP is equal to or greater than 90mmHg. The
India Clinical Trials Market: Industry Size and Growth Trends [2030] Analyzed...Kumar Satyam
According to TechSci Research report, "India Clinical Trials Market- By Region, Competition, Forecast & Opportunities, 2030F," the India Clinical Trials Market was valued at USD 2.05 billion in 2024 and is projected to grow at a compound annual growth rate (CAGR) of 8.64% through 2030. The market is driven by a variety of factors, making India an attractive destination for pharmaceutical companies and researchers. India's vast and diverse patient population, cost-effective operational environment, and a large pool of skilled medical professionals contribute significantly to the market's growth. Additionally, increasing government support in streamlining regulations and the growing prevalence of lifestyle diseases further propel the clinical trials market.
Growing Prevalence of Lifestyle Diseases
The rising incidence of lifestyle diseases such as diabetes, cardiovascular diseases, and cancer is a major trend driving the clinical trials market in India. These conditions necessitate the development and testing of new treatment methods, creating a robust demand for clinical trials. The increasing burden of these diseases highlights the need for innovative therapies and underscores the importance of India as a key player in global clinical research.
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.
Navigating Challenges: Mental Health, Legislation, and the Prison System in B...Guillermo Rivera
This conference will delve into the intricate intersections between mental health, legal frameworks, and the prison system in Bolivia. It aims to provide a comprehensive overview of the current challenges faced by mental health professionals working within the legislative and correctional landscapes. Topics of discussion will include the prevalence and impact of mental health issues among the incarcerated population, the effectiveness of existing mental health policies and legislation, and potential reforms to enhance the mental health support system within prisons.
CHAPTER 1 SEMESTER V - ROLE OF PEADIATRIC NURSE.pdfSachin Sharma
Pediatric nurses play a vital role in the health and well-being of children. Their responsibilities are wide-ranging, and their objectives can be categorized into several key areas:
1. Direct Patient Care:
Objective: Provide comprehensive and compassionate care to infants, children, and adolescents in various healthcare settings (hospitals, clinics, etc.).
This includes tasks like:
Monitoring vital signs and physical condition.
Administering medications and treatments.
Performing procedures as directed by doctors.
Assisting with daily living activities (bathing, feeding).
Providing emotional support and pain management.
2. Health Promotion and Education:
Objective: Promote healthy behaviors and educate children, families, and communities about preventive healthcare.
This includes tasks like:
Administering vaccinations.
Providing education on nutrition, hygiene, and development.
Offering breastfeeding and childbirth support.
Counseling families on safety and injury prevention.
3. Collaboration and Advocacy:
Objective: Collaborate effectively with doctors, social workers, therapists, and other healthcare professionals to ensure coordinated care for children.
Objective: Advocate for the rights and best interests of their patients, especially when children cannot speak for themselves.
This includes tasks like:
Communicating effectively with healthcare teams.
Identifying and addressing potential risks to child welfare.
Educating families about their child's condition and treatment options.
4. Professional Development and Research:
Objective: Stay up-to-date on the latest advancements in pediatric healthcare through continuing education and research.
Objective: Contribute to improving the quality of care for children by participating in research initiatives.
This includes tasks like:
Attending workshops and conferences on pediatric nursing.
Participating in clinical trials related to child health.
Implementing evidence-based practices into their daily routines.
By fulfilling these objectives, pediatric nurses play a crucial role in ensuring the optimal health and well-being of children throughout all stages of their development.
Telehealth Psychology Building Trust with Clients.pptxThe Harvest Clinic
Telehealth psychology is a digital approach that offers psychological services and mental health care to clients remotely, using technologies like video conferencing, phone calls, text messaging, and mobile apps for communication.
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.
2. -In 1940s the American Science Fiction writer Issac Asimov
published a short story that inspired generation of scientists
in the field of robotics, artificial intelligence, and computer
science.
-The birth of AI was denoted by Alan Turing's work "Computing Machinery and
Intelligence” which was published in 1950.
-In this paper, Turing asks the following question, "Can machines think?" From
there, he offers the "Turing Test", where a human interrogator would try to
distinguish between a computer and human text response. While this test has
undergone much scrutiny since its publish, it remains an important part of the
history of AI as well as an ongoing concept within philosophy as it utilizes ideas
around linguistics.
3. -Stuart Russell and Peter Norvig published in 1995, ( Artificial Intelligence: A
Modern Approach) which becomes one of the leading textbooks in the study of
AI. In it, they delve into four potential goals/definitions of AI, which
differentiates computer systems on the basis of rationality and thinking vs. acting:
Human approach:
Systems that think like humans
Systems that act like humans
-AI term was first coined in 1956 by the
American computer scientist, John
McCarthy who defined it as “the
science and engineering of creating
intelligent machines”.
Ideal approach:
Systems that think rationally
Systems that act rationally
4. Generative everything:
AI systems can now compose text, audio, and images to a sufficiently
high standard that humans have a hard time telling the difference
between synthetic and non-synthetic outputs for some constrained
applications of the technology.
STL-10 image generation benchmark
5. 1-Reactive AI
The most basic type of artificial intelligence is reactive AI, which is programmed
to provide a predictable output based on the input it receives. Reactive machines
always respond to identical situations in the exact same way every time, and they
are not able to learn actions or conceive of past or future.
● Deep Blue, the chess-playing IBM supercomputer that bested world
champion Garry Kasparov
● Spam filters for our email that keep promotions and phishing attempts out of
our inboxes
● The Netflix recommendation engine
2- Limited Memory AI
Limited memory AI uses historical, observational data in combination with pre-
programmed information to make predictions and perform complex
classification tasks.
It is the most widely-used kind of AI today.
• Autonomous vehicles use limited memory AI to observe other cars’ speed and
direction, helping them “read the road” and adjust as needed.
6. 3- Theory of Mind AI
With this type of AI, machines will acquire true decision-making capabilities that
are similar to humans.
• The Kismet robot head, developed by Professor Cynthia Breazeal, could
recognize emotional signals on human faces and replicate.
• Humanoid robot Sophia, developed by Hanson Robotics in Hong Kong, can
recognize faces and respond to interactions with her own facial expressions.
4- Self-aware AI
The most advanced as machines can be aware of their own emotions, as well as
the emotions of others around them, they will have a level of consciousness and
intelligence similar to human beings. This type of AI will have desires, needs,
and emotions as well.
7. AI is able to analyze large amounts of data stored by healthcare organizations in
the form of images, clinical research trials and medical claims, and can identify
patterns and insights often undetectable by manual human skill sets.
1- AI algorithms are taught to identify and label data patterns.
2-NLP (Natural Language Processing) allows these algorithms to isolate relevant
data.
3- With DL (Deep Learning) the data is analyzed and interpreted with the help of
extended knowledge by computers.
8. • AI technologies are showing
progress in transforming the
legacy models from being
physic AI technologies are
showing progress in
transforming the legacy models
from being physician centric to
become more patient centric.
• The healthcare sector is
undergoing rapid transformation
globally due to AI.
9. 1- AI in Diagnosis:
• AI has already been deployed in a
few hospitals to diagnose critical
diseases, such as cancer.
• Enlitic, a US based medical
imaging startup, is using deep
learning for tumor detection; its
algorithms have been designed to
detect tumors in human lungs with
the help of (CT) scan.
2- Data mining:
• AI is currently being used in data
mining of medical records.
IBM Watson Health is helping
healthcare organizations apply
cognitive technology to unlock vast
amounts of health data to power
diagnosis.
10. 3- Health assistants & Personal trainers
• AI-based chatbots are being used as health
assistants and personal trainers.
Some of the use cases of chatbots in
healthcare include scheduling doctor
appointments, providing medication
reminders, and identifying the condition
based on symptoms.
• Start-ups like Babylon Health and Your
MD are well-known AI powered healthcare
assistant applications, which helps physicians,
patients and care-givers in the above
functionalities.
• Helix, an AI start-up uses machine
learning to respond to verbal questions and
requests, thus enabling researchers to increase
efficiency, improve lab safety, stay updated
on relevant research topics, and manage
inventory.
11. 4- Drug discovery
• It is now possible to automate
drug design and compound selection
due to AI. Peptone uses AI with Keras
and TensorFlow integration to predict
protein characteristics and features to
reduce complexity in protein design,
detect production and characterization
issues.
5- Clinical trials
• AI is also widely used in clinical trials, like GNS Healthcare which uses AI
to transform diverse streams of biomedical and healthcare data into computer
models. The models enable doctors to identify patients’ responses to treatments
based on their characteristics, thereby, helping deliver personalized medicine
and treatment at scale.
12. 6- Surgical robots
• AI-powered surgical robots are currently being conceptualized by
many technology companies, by leveraging the capabilities of machine
learning applications like Google DeepMind, IBM Watson and others.
• Deploying robots with AI capabilities can result in less damage,
increased precision and speedy recovery.
• Throughout the process it will
be critical to ensure that AI does not
obscure the human face of medicine
because the biggest impediment to
AI’s widespread adoption will be
the public’s hesitation to embrace
an increasingly controversial
technology.
13.
14. -It shows that the effects of COVID-19 on AI development have multiple
perspectives. Many AI startup used machine-learning-based techniques to
accelerate COVID-related drug discovery during the pandemic.
-The AI in healthcare market is expected to be valued at USD 4.9 billion in 2020
and is likely to reach USD 45.2 billion by 2026; it is projected to grow at a
(CAGR) Compound Annual Growth Rate of 44.9% during the forecast period.
-AI investment in drug design and discovery increased significantly “Drugs,
Cancer, Molecular, Drug Discovery” received the greatest amount of private AI
investment in 2020, with more than USD 13.8 billion, 4.5 times higher than 2019.
15. - AtomNet was able to predict the binding of small molecules to proteins by
analyzing hints from millions of experimental measurements and thousands of
protein structures.
- This process enabled convolutional neural networks to identify a safe and
effective drug candidate from the database searched, reducing the cost of
developing medicine.
- The Machine Learning tools are created to draw insights from biological datasets
that are too complex for human interpretation, decreasing the risk for human bias.
Identifying new uses for known drugs is an appealing strategy for Big Pharma
companies, since it is less expensive to repurpose and reposition existing drugs
than to create them from scratch.
16. Recursion Pharmaceuticals raises $13M to discover new drugs using AI to
build complex and consolidated platforms for drug discovery platform
- AI algorithms are able to identify new drug applications, tracing their toxic
potential as well as their mechanisms of action. This technology enables the
company to repurpose existing drugs and bioactive compounds.
-By combining the best elements of biology, data science and chemistry with
automation and the latest AI advances, the founding company of this platform is
able to generate around 80 terabytes of biological data that is processed by AI
tools across 1.5 million experiments weekly.
17. - In 2015, during the West African Ebola virus outbreak, Atomwise partnered
with IBM and the University of Toronto to screen the top compounds capable
of binding to a glycoprotein that prevented Ebola virus penetration into cells in
an in vivo test.
- From the tested compounds, the one selected was chosen because it acted on
other viruses with a similar mechanism of cell penetration.
- This AI analysis occurred in less than a day, a process that would have usually
taken months or years, enabling the development of a treatment for the Ebola
virus
18. AI supports medical imaging analysis
Intro: Lung cancer is a leading cause of cancer related deaths worldwide,
accounting for up to one quarter of all cancer deaths. Because lung cancer is
diagnosed in an advanced stage, screening of early stages lung cancer has
emerged as a powerful strategy for reducing lung cancer mortality.
Problem: Chest radiography is widely used as an initial screening tool for
several important thoracic diseases that is due to its low cost, easy accessibility,
negligible radiation dose, and excellent diagnostic capability. However, the low
sensitivity of lung cancer detection (61%), low specificity (67%), substantial
inter and intra reader variability, and vulnerability to observer error remains a
persistent weakness of chest radiography as a screening tool.
Solution: Deep learning algorithms have staked out a place in lung cancer
detection on chest radiographs and have demonstrated excellent diagnostic
performance in disease enriched settings.
19.
20. Conclusion: AI has achieved:
1. Sensitivity of (91-94%)
2. Specificity of (96-100%)
21. -We are sure that A.I. is Not going to replace medical professionals.
-Due to the spectacular ability of AI in pattern recognition:
Radiology & Pathology are the most susceptible specialties to the dominance of
AI.
-it’s going to be the stethoscope of the 21st century.
-In a Forbes report, Brian Kalis, managing director of digital health and innovation
at Accenture, said:
“ AI would be widely used in US hospitals. AI has the ability to analyze big data
sets – pulling together patient insights and leading to predictive analysis. Quickly
obtaining patient insights helps the healthcare ecosystem discover key areas of
patient care that require improvement. Wearable healthcare technology also uses AI
to better serve patients”.
22.
23. -AI reduces the complications and errors that can occur during surgery and
makes the hospital stay shorter.
-AI technology is emerging as a partner to rapidly complete work, assist with
clinical decisions and improve patient outcomes.
-Primary care physicians can use AI to take their notes, analyze their
discussions with patients, and enter required information directly into EHR
systems. These applications will collect and analyze patient data and present it to
primary care physicians alongside insight into patient's medical needs.
-Applying AI in certain healthcare processes can reduce the time and resources
needed to examine and diagnose patients. With this, medical personnel can
save more lives by acting faster. Machine learning (ML) algorithms can identify
risk exponentially faster and with much more accuracy than traditional
workflows.
24. 1- Empathy cannot be replaced: the core of compassion, there is the process of
building trust, listening to the other person, paying attention to their needs,
expressing the feeling of understanding and responding in a manner that
the other person knows they were understood.
2- Physicians have a non-linear working method: Setting up a diagnosis and
treating a patient are not linear processes. It requires creativity and
problem-solving skills that algorithms and robots will never have.
3- It has never been tech vs. human : since technological innovations always
serve the purpose to help people. Collaboration between humans and technology
is the ultimate response.
25. Major restraints for the market:
1- The reluctance among medical
practitioners to adopt AI-based technologies.
2- Lack of a skilled workforce.
26.
27. 1- The increasing volume of healthcare data and complexities of datasets.
2- The intensifying need to reduce towering healthcare costs, improving
computing power and declining hardware costs.
3- Growing number of cross-industry partnerships and collaborations.
4- Rising imbalance between health workforce and patients.
5- The adoption of this technology by multiple pharmaceutical and
biotechnology companies across the world to expedite vaccine or drug
development processes for COVID-19.
28. -The use of various AI technologies can lead to unintended but harmful
consequences, such as privacy intrusion; discrimination based on gender,
race/ethnicity, sexual orientation, or gender identity; and opaque decision-making,
among other issues.
-Though a number of groups are producing a range of qualitative or normative
outputs in the AI ethics domain, the field generally lacks benchmarks that can be
used to measure or assess the relationship between broader societal discussions
about technology development and the development of the technology itself.
-Furthermore, researchers and civil society view AI ethics as more important than
industrial organizations.
-Addressing existing ethical challenges and building responsible, fair AI
innovations before they get deployed has never been more important. We should
tackle the efforts to address the ethical issues that have arisen alongside the rise of
AI applications.