A scientific talk in Staff academic seminar of KIMS & PBH, KIIT (DU), Bhubaneswar, Odisha, India. It is about the next generation aids in Medical education
This document discusses the use of artificial intelligence in medical education. It describes how AI has the potential to transform medical education through personalized learning, virtual patients and simulations, medical imaging analysis, and data-driven insights. Some benefits mentioned include adaptive assessments, virtual training scenarios to practice clinical skills safely, and access to real-world case studies and evidence-based insights. The document also outlines some challenges in implementing AI and discusses ethical considerations like bias, privacy, and the need for human oversight.
The document discusses the future of medical education and clinical training. It focuses on how artificial intelligence can be used to improve medical education in several ways. AI can help reduce the time teachers spend on tedious tasks to allow more time for meaningful instruction. It also allows for personalized education by adapting to individual student's strengths and weaknesses. AI systems can provide customized tutoring and grading of exams and essays. Feedback from AI can help educators improve course materials based on concepts students are struggling with. Students also benefit from immediate, meaningful feedback from AI without feeling shy about mistakes.
This document provides an overview of artificial intelligence and its applications in healthcare. It begins with definitions of AI and machine learning. It then reviews the history of AI from ancient times to recent developments. Current uses of AI in healthcare discussed include predictive analytics, disease detection via pattern recognition, patient self-monitoring, and scheduling. Barriers to the adoption of AI in healthcare and future applications are also mentioned.
Artificial intelligence can help improve healthcare in several ways:
1. It can help doctors make more accurate diagnoses by analyzing large amounts of medical data.
2. AI is already being used in areas like radiology to identify diseases in medical images.
3. It shows promise in personalized treatment recommendations by analyzing individual patient data.
4. In the future, AI may be able to perform some medical tasks like surgery more precisely than humans.
The document discusses the role of artificial intelligence in healthcare. It describes various aspects of AI including machine learning, knowledge engineering, robotics, and machine perception. It notes that AI has great potential to improve healthcare by helping address issues like workforce shortages and rising patient needs as populations age. However, successfully integrating AI into healthcare systems faces challenges like overcoming technical and regulatory limitations, addressing ethical concerns, and ensuring AI is used to augment rather than replace human professionals. Overall, the document presents an overview of AI in healthcare, its opportunities and challenges.
This document provides information and guidelines regarding medical electives for undergraduate medical students in India. It defines electives as optional learning experiences that allow students to explore areas of interest. The document outlines the objectives and structure of elective blocks, including topics that can be covered, requirements for attendance, supervision, and assessment. It provides templates for planning elective learning experiences and identifying potential electives in different areas like laboratories, research, clinical specialties, and community settings. The goal is to provide immersive, experiential learning opportunities to help students discover career paths and develop skills beyond their curriculum.
The Future of Medical Education From Dreams to Reality (VR, AR, AI)SeriousGamesAssoc
With three decades of e-learning experience, Dr. Levy will present innovations in technology-enhanced education from the past, present, and into the future. He will highlight some of his medical education inventions and advances including some of the first laser discs, CD-ROMs, online case-based education, 3-D anatomical and procedural animations, robotic-assisted surgery, and virtual reality surgical simulation. He will describe the role of artificial intelligence and machine learning in medical education and clinical decision support and some future work in augmented reality. It is true that what were once dreams are now reality, but there are certainly more dreams to come.
This document discusses the use of artificial intelligence in medicine. It begins by outlining how AI is rapidly being incorporated into many aspects of life. It then discusses how AI can help address challenges in global health by helping to achieve health-related sustainable development goals. The document outlines several current and potential applications of AI in medicine, such as disease diagnosis, medical imaging, and clinical trial efficiency. It also discusses both the benefits of AI, such as more accessible healthcare and improved patient outcomes, as well as some risks, such as privacy violations and algorithmic bias.
This document discusses the use of artificial intelligence in medical education. It describes how AI has the potential to transform medical education through personalized learning, virtual patients and simulations, medical imaging analysis, and data-driven insights. Some benefits mentioned include adaptive assessments, virtual training scenarios to practice clinical skills safely, and access to real-world case studies and evidence-based insights. The document also outlines some challenges in implementing AI and discusses ethical considerations like bias, privacy, and the need for human oversight.
The document discusses the future of medical education and clinical training. It focuses on how artificial intelligence can be used to improve medical education in several ways. AI can help reduce the time teachers spend on tedious tasks to allow more time for meaningful instruction. It also allows for personalized education by adapting to individual student's strengths and weaknesses. AI systems can provide customized tutoring and grading of exams and essays. Feedback from AI can help educators improve course materials based on concepts students are struggling with. Students also benefit from immediate, meaningful feedback from AI without feeling shy about mistakes.
This document provides an overview of artificial intelligence and its applications in healthcare. It begins with definitions of AI and machine learning. It then reviews the history of AI from ancient times to recent developments. Current uses of AI in healthcare discussed include predictive analytics, disease detection via pattern recognition, patient self-monitoring, and scheduling. Barriers to the adoption of AI in healthcare and future applications are also mentioned.
Artificial intelligence can help improve healthcare in several ways:
1. It can help doctors make more accurate diagnoses by analyzing large amounts of medical data.
2. AI is already being used in areas like radiology to identify diseases in medical images.
3. It shows promise in personalized treatment recommendations by analyzing individual patient data.
4. In the future, AI may be able to perform some medical tasks like surgery more precisely than humans.
The document discusses the role of artificial intelligence in healthcare. It describes various aspects of AI including machine learning, knowledge engineering, robotics, and machine perception. It notes that AI has great potential to improve healthcare by helping address issues like workforce shortages and rising patient needs as populations age. However, successfully integrating AI into healthcare systems faces challenges like overcoming technical and regulatory limitations, addressing ethical concerns, and ensuring AI is used to augment rather than replace human professionals. Overall, the document presents an overview of AI in healthcare, its opportunities and challenges.
This document provides information and guidelines regarding medical electives for undergraduate medical students in India. It defines electives as optional learning experiences that allow students to explore areas of interest. The document outlines the objectives and structure of elective blocks, including topics that can be covered, requirements for attendance, supervision, and assessment. It provides templates for planning elective learning experiences and identifying potential electives in different areas like laboratories, research, clinical specialties, and community settings. The goal is to provide immersive, experiential learning opportunities to help students discover career paths and develop skills beyond their curriculum.
The Future of Medical Education From Dreams to Reality (VR, AR, AI)SeriousGamesAssoc
With three decades of e-learning experience, Dr. Levy will present innovations in technology-enhanced education from the past, present, and into the future. He will highlight some of his medical education inventions and advances including some of the first laser discs, CD-ROMs, online case-based education, 3-D anatomical and procedural animations, robotic-assisted surgery, and virtual reality surgical simulation. He will describe the role of artificial intelligence and machine learning in medical education and clinical decision support and some future work in augmented reality. It is true that what were once dreams are now reality, but there are certainly more dreams to come.
This document discusses the use of artificial intelligence in medicine. It begins by outlining how AI is rapidly being incorporated into many aspects of life. It then discusses how AI can help address challenges in global health by helping to achieve health-related sustainable development goals. The document outlines several current and potential applications of AI in medicine, such as disease diagnosis, medical imaging, and clinical trial efficiency. It also discusses both the benefits of AI, such as more accessible healthcare and improved patient outcomes, as well as some risks, such as privacy violations and algorithmic bias.
Here is a proposed rubric to assess answers to the question "What are the antibiotics for leprosy treatment?":
4 - Identifies both rifampicin and streptomycin as first-line antibiotics for leprosy treatment. May also mention dapsone as an alternative for resistant cases. Shows understanding that rifampicin is the primary antibiotic.
3 - Identifies both rifampicin and streptomycin but does not provide context about them being first-line. May be missing detail about dapsone. Answer is largely correct but lacks some context.
2 - Identifies one of the main antibiotics (rifampicin or streptomycin) but is missing the other. May provide an incorrect or irrelevant
Role of artificial intelligence in health carePrachi Gupta
Artificial intelligence has many applications in healthcare, including improving disease diagnosis through analysis of medical imaging and other patient data, aiding radiologists in detecting abnormalities, and enabling constant remote patient monitoring. The use of AI is expected to lower medical costs through greater accuracy and better predictive analysis. It is being applied to issues like managing the coronavirus outbreak through monitoring patients and regulating hospital visitor flow. Going forward, AI may help predict where virus outbreaks are likely to occur.
CBME aims to produce competent medical graduates through an outcome-based and learner-centered approach. It assesses students based on their ability to apply knowledge and skills in real-world settings, rather than solely evaluating content recall. CBME divides competencies into observable milestones and provides formative feedback to allow for phased, self-paced learning. The goal is to develop graduates with competencies in knowledge, skills, and attitudes required for their roles as clinicians, leaders, team members, communicators, lifelong learners and professionals. Implementing CBME requires defining learning objectives, integrating topics horizontally and vertically, selecting teaching methods, and assessing students' competency levels through observations of performance.
Artificial intelligence in Health CareMuhammedIyas
This technical seminar presentation provides an overview of artificial intelligence in healthcare. It introduces artificial intelligence and how it is classified. It also discusses how AI technologies like machine learning, machine vision, and natural language processing are being used in healthcare for applications such as disease prediction, drug manufacturing, treatment decision-making, and surgery. The presentation highlights advantages of AI in healthcare like more accurate disease identification, lower treatment costs, and reduced errors. It also notes challenges around training, adoption, regulations, and security.
This document discusses the potential for artificial intelligence and machine learning in medicine. It notes that while 80% of healthcare data remains unstructured, machine learning could help analyze this data by mapping and validating data fields for modeling. However, significant preprocessing is required due to limitations in available data sets and variables. The document also discusses challenges including different classifications for patients, diseases, and representations in records. It provides an example of a study using clinical notes to predict acute kidney injury. Overall, the document outlines both the promise and challenges of applying artificial intelligence and machine learning to healthcare data.
37 slide presentation involving learning objectives, introduction, components of CBME, teaching-learning-assessment-challenges in CBME, MCI UG curriculum and its future implicability
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.
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 (AI) is an area of computer science that creates intelligent machines that work like humans. Some key activities of AI include speech recognition, learning, planning, and problem solving. John McCarthy is considered the founder of AI. AI has many applications in healthcare, including virtual assistants for unsupervised and supervised learning as well as reinforcement learning. It also has physical applications through medical devices and robots for surgery and care delivery. AI provides benefits like reducing errors, speeding decisions, and assisting humans without emotions or breaks. However, it also has disadvantages like high costs, potential job loss, and an inability to think creatively or feel empathy.
How can we make a Radiologist more efficient?
Increased Imaging for Chronic Diseases and Emergencies raise the demand for radiologists globally & AI could definitely assist them in increasing their efficiency & meet the requirements.
The document discusses clinical informatics and how it can improve healthcare. It is presented by Iris Thiele Isip Tan, a professor and chief of the UP Medical Informatics Unit. Clinical informatics uses information and technology to enhance healthcare outcomes, improve patient care, and strengthen the clinician-patient relationship. It can assemble complete patient information, apply medical knowledge, and use decision support and other technologies to improve safety and prevent errors in healthcare delivery.
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.
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 class is freshly updated for 2023 and also includes a section on the bias inherent in AI, which impacts the kind of treatment that patients receive.
Narrative writing in AETCOM by Dr Amir Maroof KhanKhan Amir Maroof
Introduction to narrative writing as per Gibb's reflective cycle.
Competency based medical education.
AETCOM module. mededu.ucms@gmail.com khanamirmaroof[at]yahoo.com
mD
The document discusses self-directed learning (SDL), which involves individuals taking initiative to diagnose learning needs, formulate goals, identify resources, implement strategies, and evaluate learning. SDL skills include developing curiosity, formulating questions, identifying needed data, locating reliable sources, and organizing information. Medical students need SDL skills to keep learning and engage in continuing education as the field rapidly advances. SDL can be facilitated in medical colleges through problem-based learning, small group teaching, and creating an autonomy-supportive environment that incorporates old and new concepts. This helps develop students' cognitive, psychomotor, and affective skills while achieving benefits like greater enthusiasm, better question-asking, and enhanced retention of knowledge. Technologies like websites, videos,
Artificial intelligence is being used in many areas of health and medicine to improve outcomes. AI can help detect diseases like cancer more accurately and at earlier stages. It is also used to analyze medical images and has been shown to spot abnormalities with over 90% accuracy. AI systems are also being developed to customize treatment plans for individuals based on their specific medical histories and characteristics. As more data becomes available through technologies like genomics and wearable devices, AI will play a larger role in precision medicine by developing highly personalized prevention and treatment strategies.
This document discusses internal and formative assessment in medical education. It defines internal assessment as assessment done by teachers who have taught a subject, and notes its benefits include overcoming day-to-day variability and allowing for larger sampling of topics. Formative assessment is defined as assessment for learning that provides ongoing feedback to both teachers and students. The key elements of effective formative assessment are identifying learning goals, involving students in self-assessment, and providing timely feedback. The document provides examples of how to incorporate more formative assessment into an existing system focused on summative assessment and internal exams.
Here are the key points about the relationship between complexity and rigor in the Common Core State Standards:
- The Standards require that students constantly build on and apply their knowledge from year to year in order to gain deep, conceptual understandings and the ability to connect key ideas.
- Students are expected to read texts of steadily increasing complexity as they progress through school. This requires continual application of their skills and continual expansion of their abilities over time.
- Tasks in the Standards promote the development of higher-order thinking skills like critical analysis, problem solving, and synthesis/creation of new understandings.
- The Standards expect students to support their analyses and arguments with evidence from texts and other sources rather than opinions or anecdotes
This document discusses several misconceptions around standardized testing and content standards. It notes that teaching to standards does not mean "teaching to the test" but rather developing complex assessments of what is most important for students to learn. It also addresses the misconception that there is too much content, pointing out standards are intended to prioritize what is most essential. The document also mentions TIMSS, an international assessment, and notes average US student performance is lower than international peers in reading, math and science. It concludes by suggesting schools focus research on improving student learning in specific units or topics.
Here is a proposed rubric to assess answers to the question "What are the antibiotics for leprosy treatment?":
4 - Identifies both rifampicin and streptomycin as first-line antibiotics for leprosy treatment. May also mention dapsone as an alternative for resistant cases. Shows understanding that rifampicin is the primary antibiotic.
3 - Identifies both rifampicin and streptomycin but does not provide context about them being first-line. May be missing detail about dapsone. Answer is largely correct but lacks some context.
2 - Identifies one of the main antibiotics (rifampicin or streptomycin) but is missing the other. May provide an incorrect or irrelevant
Role of artificial intelligence in health carePrachi Gupta
Artificial intelligence has many applications in healthcare, including improving disease diagnosis through analysis of medical imaging and other patient data, aiding radiologists in detecting abnormalities, and enabling constant remote patient monitoring. The use of AI is expected to lower medical costs through greater accuracy and better predictive analysis. It is being applied to issues like managing the coronavirus outbreak through monitoring patients and regulating hospital visitor flow. Going forward, AI may help predict where virus outbreaks are likely to occur.
CBME aims to produce competent medical graduates through an outcome-based and learner-centered approach. It assesses students based on their ability to apply knowledge and skills in real-world settings, rather than solely evaluating content recall. CBME divides competencies into observable milestones and provides formative feedback to allow for phased, self-paced learning. The goal is to develop graduates with competencies in knowledge, skills, and attitudes required for their roles as clinicians, leaders, team members, communicators, lifelong learners and professionals. Implementing CBME requires defining learning objectives, integrating topics horizontally and vertically, selecting teaching methods, and assessing students' competency levels through observations of performance.
Artificial intelligence in Health CareMuhammedIyas
This technical seminar presentation provides an overview of artificial intelligence in healthcare. It introduces artificial intelligence and how it is classified. It also discusses how AI technologies like machine learning, machine vision, and natural language processing are being used in healthcare for applications such as disease prediction, drug manufacturing, treatment decision-making, and surgery. The presentation highlights advantages of AI in healthcare like more accurate disease identification, lower treatment costs, and reduced errors. It also notes challenges around training, adoption, regulations, and security.
This document discusses the potential for artificial intelligence and machine learning in medicine. It notes that while 80% of healthcare data remains unstructured, machine learning could help analyze this data by mapping and validating data fields for modeling. However, significant preprocessing is required due to limitations in available data sets and variables. The document also discusses challenges including different classifications for patients, diseases, and representations in records. It provides an example of a study using clinical notes to predict acute kidney injury. Overall, the document outlines both the promise and challenges of applying artificial intelligence and machine learning to healthcare data.
37 slide presentation involving learning objectives, introduction, components of CBME, teaching-learning-assessment-challenges in CBME, MCI UG curriculum and its future implicability
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.
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 (AI) is an area of computer science that creates intelligent machines that work like humans. Some key activities of AI include speech recognition, learning, planning, and problem solving. John McCarthy is considered the founder of AI. AI has many applications in healthcare, including virtual assistants for unsupervised and supervised learning as well as reinforcement learning. It also has physical applications through medical devices and robots for surgery and care delivery. AI provides benefits like reducing errors, speeding decisions, and assisting humans without emotions or breaks. However, it also has disadvantages like high costs, potential job loss, and an inability to think creatively or feel empathy.
How can we make a Radiologist more efficient?
Increased Imaging for Chronic Diseases and Emergencies raise the demand for radiologists globally & AI could definitely assist them in increasing their efficiency & meet the requirements.
The document discusses clinical informatics and how it can improve healthcare. It is presented by Iris Thiele Isip Tan, a professor and chief of the UP Medical Informatics Unit. Clinical informatics uses information and technology to enhance healthcare outcomes, improve patient care, and strengthen the clinician-patient relationship. It can assemble complete patient information, apply medical knowledge, and use decision support and other technologies to improve safety and prevent errors in healthcare delivery.
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.
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 class is freshly updated for 2023 and also includes a section on the bias inherent in AI, which impacts the kind of treatment that patients receive.
Narrative writing in AETCOM by Dr Amir Maroof KhanKhan Amir Maroof
Introduction to narrative writing as per Gibb's reflective cycle.
Competency based medical education.
AETCOM module. mededu.ucms@gmail.com khanamirmaroof[at]yahoo.com
mD
The document discusses self-directed learning (SDL), which involves individuals taking initiative to diagnose learning needs, formulate goals, identify resources, implement strategies, and evaluate learning. SDL skills include developing curiosity, formulating questions, identifying needed data, locating reliable sources, and organizing information. Medical students need SDL skills to keep learning and engage in continuing education as the field rapidly advances. SDL can be facilitated in medical colleges through problem-based learning, small group teaching, and creating an autonomy-supportive environment that incorporates old and new concepts. This helps develop students' cognitive, psychomotor, and affective skills while achieving benefits like greater enthusiasm, better question-asking, and enhanced retention of knowledge. Technologies like websites, videos,
Artificial intelligence is being used in many areas of health and medicine to improve outcomes. AI can help detect diseases like cancer more accurately and at earlier stages. It is also used to analyze medical images and has been shown to spot abnormalities with over 90% accuracy. AI systems are also being developed to customize treatment plans for individuals based on their specific medical histories and characteristics. As more data becomes available through technologies like genomics and wearable devices, AI will play a larger role in precision medicine by developing highly personalized prevention and treatment strategies.
This document discusses internal and formative assessment in medical education. It defines internal assessment as assessment done by teachers who have taught a subject, and notes its benefits include overcoming day-to-day variability and allowing for larger sampling of topics. Formative assessment is defined as assessment for learning that provides ongoing feedback to both teachers and students. The key elements of effective formative assessment are identifying learning goals, involving students in self-assessment, and providing timely feedback. The document provides examples of how to incorporate more formative assessment into an existing system focused on summative assessment and internal exams.
Here are the key points about the relationship between complexity and rigor in the Common Core State Standards:
- The Standards require that students constantly build on and apply their knowledge from year to year in order to gain deep, conceptual understandings and the ability to connect key ideas.
- Students are expected to read texts of steadily increasing complexity as they progress through school. This requires continual application of their skills and continual expansion of their abilities over time.
- Tasks in the Standards promote the development of higher-order thinking skills like critical analysis, problem solving, and synthesis/creation of new understandings.
- The Standards expect students to support their analyses and arguments with evidence from texts and other sources rather than opinions or anecdotes
This document discusses several misconceptions around standardized testing and content standards. It notes that teaching to standards does not mean "teaching to the test" but rather developing complex assessments of what is most important for students to learn. It also addresses the misconception that there is too much content, pointing out standards are intended to prioritize what is most essential. The document also mentions TIMSS, an international assessment, and notes average US student performance is lower than international peers in reading, math and science. It concludes by suggesting schools focus research on improving student learning in specific units or topics.
[DSC Europe 22] Machine learning algorithms as tools for student success pred...DataScienceConferenc1
The goal of higher education institutions is to provide quality education to students. Predicting academic success and early intervention to help at-risk students is an important task for this purpose. This talk explores the possibilities of applying machine learning in developing predictive models of academic performance. What factors lead to success at university? Are there differences between students of different generations? Answers are given by applying machine learning algorithms to a data set of 400 students of three generations of IT studies. The results show differences between students with regard to student responsibility and regularity of class attendance and great potential of applying machine learning in developing predictive models.
The document summarizes key points from a discussion on reimagining authentic curriculum and assessment in the age of generative AI. It includes:
1. Three major challenges are contract cheating, impersonation, and generative AI which can produce written work.
2. There are opportunities to use AI to enhance student learning and productivity if designed appropriately. Students could become creators by using AI to aid understanding or produce new learning resources.
3. Authentic assessment needs to move beyond essays and emphasize real-world skills through activities like presentations that cannot be produced by AI as well as balancing written work with other assessments.
Big data has the potential to transform nursing education and healthcare. It allows analysis of large, diverse datasets to reveal patterns and trends. Nursing has a long history of using data to improve patient care. Now, with big data and analytics, insights can be gained from vast amounts of structured and unstructured data from various sources. This can help personalize learning and predict outcomes. However, challenges include technical issues, privacy concerns, and developing a data-driven culture. With collaboration across sectors and letting the data speak, big data can advance nursing knowledge and the learning healthcare system.
Health information professionals and Artificial Intelligencecoxamcoxam
The document discusses the impact of artificial intelligence (AI) on health information professionals and their work. It provides 5 definitions of AI, from everyday tools that increase productivity to a global industrial complex. It explores both opportunities and risks of using AI, such as privacy concerns, bias, lack of transparency, and ethics. The document also examines how AI may change information professional jobs and skills needed, such as data management and literacy. Finally, it discusses a vision for an "intelligent library" powered by AI and the user's interactions within it.
ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION A BIBLIOMETRIC ANALYSIS OF RESEAR...Swarup Adhikary
This study conducted a bibliometric analysis of research trends related to artificial intelligence (AI) in higher education. The analysis found that the number of publications on this topic has steadily increased between 2014-2023, with the most common subject area being social science. The United States was found to be the most productive country. The author with the most publications was Salas-Rueda, while the most influential authors based on citations were Zawacki-Richter et al. The University of Oldenburg and Universidad Nacional Autónoma de México were the most influential and most productive institutions, respectively. Artificial intelligence was the most frequently used keyword.
Created this past May as a means to raise the awareness of educators and innovators in Mississippi about the future of education and how AI, Big Data, Virtual Reality, self-paced eLearning, Intelligent virtual classroom environments and telecommunications will change educational practice.
Expo Day: Neuroenginnering, BPI, Arrowsmith Program & ARPFSharpBrains
Selected Summit Sponsors and Partners showcase their most promising brain health & enhancement initiatives and solutions.
Noon-1pm. From tomorrow’s neuroengineering to today’s brain health
*Dr. Randal Koene, Lead Scientist at Kernel, discusses future directions of neuroenginnering and human computer interfaces.
*Dr. Leanne Young, Executive Director of the Brain Performance Institute at UT-Dallas Center for BrainHealth presents the new 62,000-square-foot Brain Performance Institute.
1-1.30pm. Debbie Gilmore, Executive Director of The Arrowsmith Program, will present plans to better equip 100+ schools helping students with special needs.
1.30-2pm. Dr. Chris Walling, Chairman of the Educational Advisory Committee at The Alzheimer’s Research and Prevention Foundation (ARPF), will present the new Brain Longevity Therapy Training.
*Álvaro Fernández, CEO and Editor-in-Chief of SharpBrains
*Sarah Lenz Lock, Senior Vice President for Policy at AARP and Executive Director of the Global Council on Brain Health (GCBH)
*Dr. April Benasich, Director of the Baby Lab at the Rutgers Center for Molecular and Behavioral Neuroscience
*Chaired by: Dr. Cori Lathan, Co-Chair of the World Economic Forum’s Council on the Future of Human Enhancement
Slidedeck supporting session held during the 2017 SharpBrains Virtual Summit: Brain Health & Enhancement in the Digital Age (December 5-7th). Learn more at: https://sharpbrains.com/summit-2017/
Sankey, M. 2023. Embracing AI for student and staff productivity. THETA 2023 Making Waves. Brisbane Convention Centre. Brisbane. 16-19 April.
Abstract: ChatGPT, and more broadly AI Transformers, has put the cat among the pigeons over recent months. Institutions are looking at different ways to provide the best possible advice to our staff and students. There is now consistent agreement, there can potentially be very positive outcomes for both students and staff, but we first need to understand this as a community. The theme of the ACODE 88 Meeting 2 March 2023 was ‘Embracing AI for student and staff productivity’. As this workshop we had some 200 participants; Director of TEL, Managers and Educational Designers, all bringing perspectives from their own institutions, to benchmark and understand were we stand on this complex, but exciting issue. As an output from this workshop, ACODE have developed a White paper, to help provide the sector with a way forward, one developed together.
Artificial Intelligence Tools for Students with Learning DisabilitiesJohn Rochford
AI is transforming education worldwide. The promise is great. The reality is not. Training and development of online AI tools do not include students with learning disabilities. Why? What are we doing? What can we do better?
A New Paradigm on Analytic-Driven Information and Automation V2.pdfArmyTrilidiaDevegaSK
The document proposes an end-to-end methodology for developing analytic-driven information and automation systems based on big data, data science, and artificial intelligence. The methodology involves 6 steps: 1) collecting data from multiple sources, 2) preprocessing the data, 3) extracting features from the data, 4) clustering and interpreting the data, 5) designing applications, and 6) implementing and evaluating the systems. It then provides an example of applying this methodology to develop an early warning system for monitoring higher education institutions in Indonesia. The system would collect data from various sources, analyze it using machine learning techniques, predict and prescribe interventions for student groups.
SGCI-URSSI-Sustainability in Research ComputingSandra Gesing
Sustainability in research computing has many facets such as funding and career paths for facilitators and research software engineers. The concern about sustainability is addressed in projects like the Science Gateways Community Institute (SGCI) and the conceptualization of the US Research Software Sustainability Institute (URSSI). Many further initiatives and projects are concerned with sustainability and the discussion at the ACI-REF VR Intermediate Workshop led to some consolidation ideas.
This document announces a 5-day faculty development program on data science and its applications from December 6-10, 2021. The FDP will be organized by the Department of Computer Science and Engineering at Lakireddy Bali Reddy College of Engineering and is sponsored by AICTE Training and Learning Academy. The FDP aims to provide an overview of data science concepts through hands-on exercises in topics like natural language processing, computer vision, graph neural networks, and medical data analytics. Eligible participants include faculty, researchers, and students. Registration is free and open until December 2 on the AICTE portal. A test will be conducted at the end and certificates will be awarded based on attendance and exam score.
This document discusses the challenges higher education faces in adopting data-driven strategies and the key ingredients needed to do so effectively. It outlines the goals of improving efficiency, student success, teaching methods, and using data to inform decisions. While progress has been made in analytics and evidence-based decision making, adoption is not as fast as desired due to issues like the nature of teaching, administering a university, and human nature. The document recommends establishing a culture of information sharing, integrating student data systems, ensuring analytics systems are fast and comprehensive, and collaborating with partners to address this complex problem.
Scholar Plot –
Scalable Data Visualization Methods for Academic Careers
Kyeongan (Karl) Kwon
PhD Dissertation
Department of Computer Science
University of Houston
Monday July 18, 2016
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This presentation is targeted for MBBS, MD and BDS students that describes briefly about aetiopathogenesis, tumour markers, anti cancer agents, apoptosis
RNA comes in several types that serve different functions. Messenger RNA (mRNA) acts as a template for protein synthesis by carrying genetic code from DNA to the ribosomes. Transfer RNA (tRNA) transfers amino acids to the ribosome during protein synthesis. Ribosomal RNA (rRNA) is a core component of ribosomes and catalyzes peptide bond formation. Other non-coding RNAs include microRNAs (miRNAs) that regulate gene expression at the post-transcriptional level, and small nuclear RNAs (snRNAs) that are involved in splicing mRNA transcripts. RNAs play essential roles in coding, decoding, regulating, and expressing genes.
RNA metabolism and transcription are complex processes involving multiple steps. There are three major types of RNA - mRNA, rRNA and tRNA. Transcription involves initiation, elongation and termination. It requires a DNA template, RNA polymerase enzyme, and nucleotide substrates. Prokaryotes have a single RNA polymerase while eukaryotes have three specialized RNA polymerases. Transcription results in primary transcripts that undergo extensive processing before becoming functional RNAs. Alternative splicing allows generation of multiple mRNAs from a single gene. Transcription and its regulation play an important role in gene expression.
This document discusses the organization and structure of DNA. It notes that DNA is highly compressed through winding around histone proteins to form nucleosomes. Histone chaperones assist in nucleosome formation. Nucleosomes are arranged differently in transcriptionally active versus inactive regions of DNA. Euchromatin, which is actively transcribed, replicates earlier than heterochromatin, which is transcriptionally silent. The document also discusses repetitive sequences in DNA, including transposable elements, microsatellites, and trinucleotide repeats linked to genetic diseases. Pseudogenes and gene rearrangements are mentioned as well.
The document summarizes key facts about DNA and its structure. It notes that it takes 8 hours for a cell to copy its DNA, which contains about 30 billion nucleotide base pairs on each strand. If total human DNA was laid end to end, it would stretch to the sun and back over 600 times. Our genes are highly similar to other organisms, with over 90% similarity to mice. DNA is made up of nucleotides containing phosphate groups, deoxyribose sugars, and nitrogenous bases of A, T, C, or G. The double helix structure of DNA involves base pairing and hydrogen bonding between strands in an antiparallel fashion.
Glycine is an aliphatic amino acid which gives rise to many vital derivatives. This is a non-essential amino acid. This presentation is targeted for MBBS, MD, BDS and general Biochemistry students.
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
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إضغ بين إيديكم من أقوى الملازم التي صممتها
ملزمة تشريح الجهاز الهيكلي (نظري 3)
💀💀💀💀💀💀💀💀💀💀
تتميز هذهِ الملزمة بعِدة مُميزات :
1- مُترجمة ترجمة تُناسب جميع المستويات
2- تحتوي على 78 رسم توضيحي لكل كلمة موجودة بالملزمة (لكل كلمة !!!!)
#فهم_ماكو_درخ
3- دقة الكتابة والصور عالية جداً جداً جداً
4- هُنالك بعض المعلومات تم توضيحها بشكل تفصيلي جداً (تُعتبر لدى الطالب أو الطالبة بإنها معلومات مُبهمة ومع ذلك تم توضيح هذهِ المعلومات المُبهمة بشكل تفصيلي جداً
5- الملزمة تشرح نفسها ب نفسها بس تكلك تعال اقراني
6- تحتوي الملزمة في اول سلايد على خارطة تتضمن جميع تفرُعات معلومات الجهاز الهيكلي المذكورة في هذهِ الملزمة
واخيراً هذهِ الملزمة حلالٌ عليكم وإتمنى منكم إن تدعولي بالخير والصحة والعافية فقط
كل التوفيق زملائي وزميلاتي ، زميلكم محمد الذهبي 💊💊
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A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
2. We’ll discuss……
• How education system has evolved and Medical education per
se
• What is Artificial intelligence (AI)
• Who and how it was conceptualized
• Types
• Role of AI in Medical education
• AI in Skill lab
• The AI doctor
• Role of AI in research
• Are we future ready???
7/15/2021
Staff academic seminar KIMS
5. What is Artificial intelligence??
7/15/2021
Staff academic seminar KIMS
Artificial intelligence is the development of computer
systems that are capable of performing tasks that
normally requires human intelligence, such as decision
making, object detection, solving complex problems
and so on
6. Staff academic seminar KIMS
“[AI] is going to change the world more than anything in the history of
mankind. More than electricity.”— AI oracle and venture capitalist Dr.
Kai-Fu Lee, 2018
7/15/2021
Father of AI- John Mc Carthy
7. Types of AI
• Logic-based--Algorithmic
– 1955-1975: Computer is a universal logical machine; it is able to
do what is instructed by humans
●Knowledge-based; representational
– 1970-1990: In between algorithm and AI, still have to write
programs to achieve what we intend to do by AI
● Data-driven
– 1930-1965 --- 1985-1990 --- 2005-present
– Machine learning algorithms that minimize prediction or clustering
error
– Known as artificial neural networks and machine learning
7/15/2021
Staff academic seminar KIMS
8. Machine learning—Instead of telling “how to do things”,
you say “what your goal” is
7/15/2021
Staff academic seminar KIMS
• Requires millions of examples
• Requires cheap parallel processing and
new hardware
• Requires data- internet connectivity
• Enabled by open source development
tools and freely accessible”pre-
trained” machine learning
models (from Google et al.)
10. What we call “Future” , will be shaped by
“present”
7/15/2021
Staff academic seminar KIMS
11. The instructivist
• Machine generates questions as per
the info fed into it
• Dialogue based tutoring- Quiz, tests-
Alexa, audio books
• Language-learning app- Can convert
instructions from any language to your
choiceable language
7/15/2021
Staff academic seminar KIMS
12. The constructivist (Student-supporting)
• Exploratory learning
environment
• Writing evaluation
• AI collaborative learning
• Course recommendation
• Analytics
• AI learning companions-Viva
app
7/15/2021
Staff academic seminar KIMS
13. Teacher supporting
• AI teaching assistant
• Automatic test generation
• Creating OER (Open educational resources)
• Monitoring student performances, analytics
• Monitoring student attention and emotion
• Plagiarism check
7/15/2021
Staff academic seminar KIMS
14. System supporting
• Educational data mining for resource
allocation
• Performance analytics
• Synthetic teachers
• Aide in diagnosis
• Telemedicine
• Research tool
7/15/2021
Staff academic seminar KIMS
16. AI as an aide in diagnosis and decision making
• The sooner we learn, the better
• AI –assisted diagnostics- image analysis for Pathology
• Auto verification of Biochemical reports
• Triage on the basis of chatbots
• AI-enhanced microscopes
• Radiology imaging
• Patient scheduling- less patient waiting time
7/15/2021
Staff academic seminar KIMS
17. AI as a research tool
• Big data analysis
• For better decision making and apt care
• In silico drug designing
• Genomic studies
• Neural network in clinical trials
7/15/2021
Staff academic seminar KIMS
18. What the teachers found after using AI tools
7/15/2021
Staff academic seminar KIMS
19. Indian Data an on 16th Feb 2021 :
• Total no of Medical Colleges – 562
( Govt. MC - 286 & Private MC – 276 )
No. of MBBS Seats – 84649
No. of PG Seats – 42182
No. of DNB Seats – 9795
No. of FNB Seats – 2432
No. of Ayurvedic Students (BAMS) – 2340
No. of Homeopathy Students (BHMS) – 3589
20. TRANSHUMANISM- CYBORGS/ CYBERNETIC CREATURES
Can an AI doctor perform better??
7/15/2021
Staff academic seminar KIMS
To be a competent doctor AI has to be better
than only the worst graduating student in your class.
Further, assuming a standard distribution curve, if AI is
better than your average student, it is better than 50%
of all doctors.
How confident are we in other aspects of
all your graduating students, such as their principles
and ethics?
The
The HUMANTOUCH
21. वयं राष्ट्रे जागृयाम पुरोहितााः स्वािा
May we, the leaders, remain
awake in the Rāṣṭra and for
the Rāṣṭra.