Machine Learning for Personalized Healthcare - Opportunities, Challenges and Insights

Explore the opportunities, challenges, and insights of machine learning in personalized healthcare through this special ECE seminar featuring speakers from Microsoft Research Cambridge. Delve into the application of AI in healthcare, covering topics such as disease subtype discovery, stratified interventions, and tailored interaction sequences. Examine case studies in mental health, respiratory disease, and critical care settings to understand the practical implications of machine learning in healthcare delivery. Learn about probabilistic models for asthma and allergy management, optimal policies for invasive mechanical ventilation, and frameworks for lab test ordering. Gain valuable insights into the potential of AI to revolutionize healthcare while considering the inherent challenges in leveraging these technologies for actionable outcomes.

Introduction
Opportunities and Challenges
Challenges
General philosophy
Probabilistic model
Asthma and allergy
Three models
Implications for personalization
Introductions
Invasive Mechanical Ventilation
Optimal Policy
Optimal Policy Example
Frameworks
Lab Test Ordering
Vectorvalued Reward Function
Reward Function Selection
Conclusion
Next Steps
Project Talia