Innovating Medical-Education with AI Final-2.pptx

Innovating Medical Education using AI, Agents, LLMs, and deep learning. The benefits and dangers of AI are explored. Popular tools for faculty presented. The possibilities of new faculty/student interaction using Precision Education are offered. Various video excerpts from important innovators is embedded.

1. Innovating Medical Education with AI Sa Stafford L Battle Generated with the assistance of Artificial Intelligence Agents

2. Disclosure I have nothing to disclose.

3. Learning Objectives Discuss Artificial Intelligence, Machine Learning, Deep Learning and AI Agents Create teaching strategies with Generative AI Enhance the faculty-student relationship Take Advantage of Precision Medical Education and Diversity Improve Diagnostic Accuracy Discover some of the best AI tools for doctors Identify Organizations that offer AI assistance to Faculty

4. AI is revolutionizing medical education, enabling personalized learning , improving diagnostic accuracy, streamlining workflows, and enhancing simulation-based training.

5. Artificial Intelligence is Rapidly Transforming Learning and Teaching . . . Educators must adapt now . . .

6. Agents Agents Agents

7. Dr. Bernard S. Chang, the Dean for Medical Education at Harvard Medical School, believes that artificial intelligence (AI) is poised to transform medical education. He argues that medical schools should not only embrace AI but also take an active role in shaping its development and use.

8. Students still need to learn the fundamentals of being a doctor, Generative AI can accelerate their progress toward higher levels of cognitive analysis, nuanced patient understanding, compassionate communication, and culturally competent care.

9. Precision Medical Education

10. Empowering Educators 1 Student Performance Tracking AI-powered analytics monitor student progress, identify learning difficulties, and provide early intervention opportunities. 2 Curriculum Optimization AI insights guide educators in refining course content, teaching methods, and assessment strategies to better align with student needs. 3 Personalized Interventions AI recommendations enable educators to develop targeted support programs and personalized learning plans for struggling students.

11. Personalizing the Med School Experience Adaptive Learning AI algorithms analyze student performance and learning patterns to tailor content and pacing, ensuring each individual receives the optimal learning experience. Virtual Mentors Intelligent chatbots and virtual assistants provide personalized guidance and feedback, offering students 24/7 access to expert-level support. Precision Assessments AI-powered assessments pinpoint strengths and weaknesses, allowing educators to develop targeted interventions and personalized learning plans.

12. Advancing Simulation-Based Training Realistic Scenarios AI-powered simulation systems create highly realistic and immersive medical scenarios, allowing students to practice critical skills in a safe environment. Real-Time Feedback Intelligent feedback systems analyze student performance in simulations and provide actionable insights to guide their learning and skill development. Data-Driven Insights AI collects and analyzes simulation data to identify skill gaps, evaluate training effectiveness, and inform curriculum development.

13. Enabling Remote and Virtual Learning Distance Learning AI-powered virtual classrooms and interactive simulations allow medical students to engage in rich learning experiences from anywhere. Telehealth Integration AI-driven telehealth platforms facilitate remote consultations, virtual examinations, and remote patient monitoring, enhancing access to medical care. Data-Driven Insights AI analyzes student engagement, performance, and feedback data to continuously improve virtual and remote learning programs.

14. Enhancing Diagnostic Accuracy 1 Computer-Aided Diagnosis AI algorithms analyze medical images, patient data, and symptoms to provide accurate and early detection of conditions, enabling quicker interventions. 2 Decision Support Systems AI-powered decision support tools synthesize vast amounts of medical knowledge, clinical guidelines, and patient data to assist clinicians in making informed decisions. 3 Predictive Analytics AI models forecast disease progression, treatment outcomes, and potential complications, empowering medical professionals to proactively manage patient care.

15. Streamlining Administrative Tasks Automated Documentation AI-driven medical documentation tools generate accurate and comprehensive patient records, reducing administrative burdens on healthcare providers. Intelligent Scheduling AI algorithms optimize appointment scheduling, resource allocation, and workflow management, enhancing efficiency and productivity in medical settings. Intelligent Assistants (Agents) AI-powered virtual assistants handle routine inquiries, freeing up medical staff to focus on more complex and patient-centric tasks.

16. AI Tools For Doctors 1. Clinical Decision Support Systems (CDSS) Examples: IBM Watson, Oncology Expert Advisor, VisualDx AI-powered systems can assist doctors in making accurate diagnoses, treatment recommendations, and identifying potential risks or contraindications based on patient data and medical knowledge. 2. Medical Imaging Analysis Examples: Viz.ai , Aidoc , Zebra Medical Vision Algorithms can analyze medical images like X-rays, CT scans, and MRI scans, helping doctors detect and prioritize potential abnormalities or findings that may require further investigation.  

17. 3. Natural Language Processing (NLP) for Documentation Examples: Nuance Dragon Medical, M*Modal, AMC Health NLP-powered speech recognition and documentation tools can help doctors create accurate and comprehensive patient notes, streamlining the documentation process and reducing administrative burdens. 4. Drug Discovery and Repurposing Examples: IBM RXN for Chemistry, Atomwise , Insilico Medicine AI can be used to analyze vast datasets and identify potential drug candidates, predict drug interactions, and suggest repurposing opportunities, aiding in the development of new treatments.  

18.    5. Patient Monitoring and Predictive Analytics: Examples: Viz.ai, Biofourmis , Philips HealthSuite Algorithms can monitor patient data (vital signs, lab results, sensor data) and provide early warnings for potential adverse events, enabling proactive interventions and personalized care.   6. Medical Research and Literature Search: Examples: Semantic Scholar, DeepResearchSearch , IBM Watson for Drug Discovery AI-powered search engines and tools can help doctors quickly find relevant medical literature, research papers, and clinical trials, supporting evidence-based decision-making and staying updated with the latest advancements.

19.      7. Virtual Assistants and Chatbots: Examples: Ada Health, Babylon Health, Your.MD AI-powered virtual assistants and chatbots can provide patients with personalized health information, triage services, and guidance on when to seek professional medical attention, potentially reducing the burden on healthcare systems.

20. Responsible AI Implementation Ethical Considerations Ensuring AI systems adhere to ethical principles, protect patient privacy, and mitigate biases to maintain trust and accountability. Transparency and Explainability Developing AI models that are transparent and explainable, allowing for better understanding and oversight of decision-making processes. Ongoing Monitoring and Regulation Establishing robust governance frameworks and continuous monitoring to ensure the responsible and appropriate use of AI in medical education.

21. Will AI Replace the Human Element?

22. Professional organizations and institutions provide essential information about the latest AI applications, best practices, and ethical considerations .

23. Howard University

24. In Conclusion

25. Thank You! Contact Information Stafford L Battle Office of Curriculum Howard University College of Medicine [email protected] [email protected] http://www.sbattle.org http://www.staffordbattle.org http://www.afrocyberspace.org Q & A