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.

1. AI in Medical Education
An evolving Paradigm
By
Dr Lokendra Sharma
Founder and Ex-Principal , Alwar Medical College
Professor and Head, Dept. Of Pharmacology,RUHS-CMS

2. AI technology has
the potential to
transform medical
education
Benefits of using
AI in medical
education
Introduction to AI in Medical Education
Challenges and
limitations of AI in
medical
education

3. AI technology has the potential to transform medical education
This presentation explores how artificial intelligence is shaping medical
education and revolutionizing patient care.
It covers personalized learning, virtual patients and simulations,
medical imaging analysis, and data-driven insights.
Join us to learn how AI is empowering future healthcare professionals
with advanced tools and insights.
Introduction to AI in Medical Education

4. Imagine a medical
student, using an
AI-driven platform.
This platform
analyzes their
learning patterns,
adapting lessons
and quizzes to
his/her pace.
Personalized Learning
As the student
progresses, the
system refines its
recommendations,
optimizing his/her
understanding and
retention of
complex medical
concepts.

5. AI-driven
assessments adapt
to a student's
performance,
challenging them
with appropriate
questions.
Immediate
feedback helps
learners identify
areas for
improvement.
Adaptive Assessments
This approach
encourages active
engagement with
the material.

6. Virtual Patients and Simulations
Next, we have virtual patients and
simulations.For example lets now imagine
another student.
With AI-powered simulations, he/she
practices diagnosing and treating virtual
patients in lifelike scenarios.
These simulations help him/her refine his/her
clinical skills, decision-making abilities, and
even emotional intelligence, all within a safe

7. Medical Imaging Analysis
AI algorithms excel at interpreting X-rays, MRIs, and
CT scans.
A medical student, benefits from this technology by
gaining exposure to a broad range of cases.
They will learn to identify anomalies and correlate them
with diagnoses, preparing them for real-world patient
encounters.

8. Data-Driven
Insights
• As a future doctor, access to
AI-powered databases to
study real-world case studies
will be transformative .
• AI extracts valuable insights
from patient records, helping
to understand treatment
outcomes and trends.
• This evidence-based approach
will guide decision-making
process.

9. 01
02
Language Processing and
Documentation
This automation streamlines
administrative tasks, giving
medical students more time to
focus on learning and patient
care.
AI-powered language
processing tools assist
students in transcribing and
summarizing patient
encounters.

10. Virtual Anatomy
● AI facilitates the creation of highly
detailed virtual anatomical models.
● Students can explore the human body in
three dimensions, enhancing their
understanding of anatomy.
● This immersive experience aids in the
development of surgical skills and
procedures.

11. Telemedicine and Remote Learning
● AI enables telemedicine
experiences and remote learning
opportunities.
● Medical students can participate
in virtual clinical rotations,
consultations, and surgeries.
● This expands their exposure to
diverse medical scenarios.

12. IBM Watson for Oncology ?

13. 01
02
03
It analyzes patient
data against a vast
database of
medical knowledge.
IBM Watson for Oncology
IBM Watson for
Oncology assists
oncologists in making
treatment decisions
for cancer patients.
Personalized
treatment
recommendation
s are provided
based on the
specific patient's
profile.

14. Efficiency and Insight in Oncology
Education
● IBM Watson for Oncology makes the
learning process more efficient and
insightful.
● It analyzes patient data and provides
treatment recommendations based on
the latest research and treatment
protocols.

15. AI in Deep Genomics ?

16. Some Notable Real World AI
Applications already in use
1. Deep Genomics:It utilizes
artificial intelligence and
machine learning to analyze
genetic data and uncover
insights into the impact of
genetic variations on human
health.

17. Some Notable Real World AI
Applications already in use
2. Freenome: is a health
technology eatablishment
that specializes in early
cancer detection through
the analysis of blood
samples, employing
advanced computational
techniques to identify
disease-associated patterns.

18. Some Notable Real World AI
Applications already in use
3. Buoy Health: Buoy Health
offers an AI-powered digital
health platform that assists
users in assessing their
symptoms and provides
personalized
recommendations for
appropriate healthcare
actions.

19. Path AI ?

20. Some Notable Real World AI
Applications already in use
4. PathAI: PathAI is a
establishment focused on
enhancing pathology
through artificial intelligence.
They develop AI-powered
solutions to aid pathologists
in diagnosing diseases
accurately from medical
images.

21. Augmadix ?

22. Some Notable Real World AI
Applications already in use
5. Augmedix: Augmedix is a
healthcare technology company
that streamlines doctor-patient
interactions by using wearable
technology to automatically
document medical visits and
create accurate electronic
health records.

23. Niramai?

24. Some Notable Real World AI
Applications already in use
6. Niramai: Niramai is a startup
that employs thermography
and AI for early breast
cancer detection, offering a
non-invasive and privacy-
sensitive solution.

25. Tricog ?

26. Some Notable Real World AI
Applications already in use
7. Tricog: Tricog is a healthcare
technology establishment that has
developed an AI-driven platform to
help doctors diagnose and treat
cardiovascular diseases more
effectively by quickly analyzing
ECG results.

27. HealthifyMe ?

28. Some Notable Real World AI
Applications already in use
8. HealthifyMe: HealthifyMe is a
wellness and fitness app that
employs AI to offer personalized
diet, fitness, and weight
management plans, making
healthy living more accessible and
achievable.

29. Qure.ai ?

30. Some Notable Real World AI
Applications already in use
9. Qure.ai: Qure.ai specializes
in medical imaging
interpretation through AI
algorithms, aiding
healthcare professionals in
diagnosing diseases like
tuberculosis and head
injuries more efficiently.

31. Med-PaLM2 ?

32. Some Notable Real World AI
Applications already in use
• 10. Med-PaLM2- Med-PaLM is a large
language model (LLM) designed to provide
high quality answers to medical questions.
• Med-PaLM harnesses the power of Google’s
large language models, which we have aligned
to the medical domain and evaluated using
medical exams, medical research, and
consumer queries.
• The first version of Med-PaLM, preprinted in late
2022 and published in Nature in July 2023,
was the first AI system to surpass the pass
mark on US Medical License Exam (USMLE)

35. Scope for AI is in Every step of
PV

36. • It will decreasing the
cost of case
processing
improving data quality
Repetitive and routine
manual tasks can be
automated and tackled
byAI

37. MAIN SOURCES OF PV
TRAINING DATA
• VigiBase- A PV database that records
the information in a structured and
ordered form to allow easy analysis of
recorded data.
This system is related to medical and drug classification
• VigiAccess- It is a publicly accessible
web application to browse and access
the data of adverse drug effects easily
through VigiBase.
VigiBase/VigiAccess/VigiFlow/Vigi
Lyse Training Session at
RUHS-CMS

38. MAIN SOURCES OF PV
TRAINING DATA
VigiLyze- online resource that provides
a clear and quick review of VigiBase which
can be explored online for further analysis
VigiFlow- web-based management system
for international drug monitoring by:
• Collection
• Processing and Sharing of data
VigiBase/VigiAccess/VigiFlow/Vigi
Lyse Training Session at
RUHS-CMS

39. AI integration in Pharmacovigilance,Emergency
Medicine training, self-guided learning and
management
• Work done in RUHS is being recognized internationally
• We at Department of pharmacology are integrating our
experiences from the work in AI, in self guided stressless
learning including Emergency Medicine training.

40. 01
02
03
Future of AI in Medical
Education
Collaborative opportunities for
AI and educators in medical
education
Advancements in AI
technology for medical
education
Integration of AI with
traditional teaching methods

41. Some
examples of
AI in Medical
Education
• Interactive Virtual Patient
• Quizlet
• ChatGPT

42. ChatGPT’s Features for Personalized Learning:

43. Is AI all
the same?
● AI too has diversity
depending upon the
tasks it is designed for

44. AI or not
AI
● Personalized
suggestions

45. AI or not
AI
• Image processing
and enhancements
• Deep fakes

46. AI or not
AI
● Spreadsheet and data
analysis without human
input

47. AI or not AI
● Mental Health
Disorders
Project(GMHAT) with
Jointly SMS Medical
College Jaipur and
University of
Manchester (UK)
● https://gmhat.org

48. 01
02
03
Bias and fairness
in AI algorithms
Ethical Considerations in AI-based Medical
Education
Data privacy and
security concerns
Human supervision
and oversight in AI-
driven education

49. Thank you. Please feel free to ask any questions. 😄