Despite the importance of human health, we do not fundamentally understand what it means to be healthy. Health is unlike many recent machine learning success stories - e.g., games or driving - because there are no agreed-upon, well-defined objectives. In this talk, Dr. Marzyeh Ghassemi will discuss the role of machine learning in health, argue that the demand for model interpretability is dangerous, and explain why models used in health settings must also be "healthy". She will focus on a progression of work that encompasses prediction, time series analysis, and representation learning.
- A Review of Challenges and Opportunities in Machine Learning for Health
- Clinical Intervention Prediction and Understanding Using Deep Networks
- Clinically Accurate Chest X-Ray Report Generation
- Can AI Help Reduce Disparities in General Medical and Mental Health Care?
- Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings
- ClinicalVis: Supporting Clinical Task-Focused Design Evaluation