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Syllabus
Calendar
Week 1 - Intro
M1 - Clinical AI
- Clinical AI Part I
- Clinical AI Part II
M2 - Trustworthy & Efficient AI
- Trustworthy & Efficient AI Part I
- Trustworthy & Efficient AI Part II
M3 - Graph Learning
- Biomedical Graph Learning Part I
- Biomedical Graph Learning Part II
M4 - Language Modeling
- Medical Language Modeling Part I
- Medical Language Modeling Part II
M5 - Biomedical Imaging
- Biomedical Imaging Part I
- Biomedical Imaging Part II
Week 12 - Ethical & Legal
M6 - Generative AI
- Generative AI Part I
- Generative AI Part II
Staff
Schedule

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Canvas
Harvard DBMI
Zitnik Lab

Week 1 - What Makes Biomedical Problems Unique

Required Reading

How machine learning will transform biomedicine
Do no harm: a roadmap for responsible machine learning for health care

Optional Reading

Medical ethics considerations on artificial intelligence
Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities
A unified framework of five principles for AI in society
Big data in healthcare: Using analytics to identify and manage high-risk and high-cost patients
Safeguards for human studies can’t cope with big data