BMI 702 | Biomedical Artificial Intelligence
Harvard - Foundations of Biomedical Informatics II, Spring 2023
Artificial intelligence is poised to enable breakthroughs in science and reshape medicine. This introductory course provides a survey of artificial intelligence for biomedical informatics, covering methods for key data modalities: clinical data, networks, language, and images. It introduces machine learning problems from a practical perspective, focusing on tasks that drive the adoption of machine learning in biology and medicine.
It outlines foundational algorithms and emphasizes the subtleties of working with biomedical data and ways to evaluate and transition machine learning methods into biomedical and clinical implementation. An important consideration in this course is the broader impact of artificial intelligence, particularly topics of bias and fairness, interpretability, and ethical and legal considerations when dealing with artificial intelligence.
Week 1
Course overview and introduction to biomedical AI
- Jan 23
- Jan 24
- QuizWeek 2 pre-class quiz (due Jan 29)
- Canvas
Week 2
Clinical research using EHR data, subtype discovery, disease diagnosis and prognosis prediction
- Jan 30
- Module 1LectureClinical AI Part I
- Slides, Reading List
- Jan 31
- QuizWeek 3 pre-class quiz (due Feb 5)
- Canvas
Week 3
Multi-institutional EHR systems, transfer learning, federated learning, clinical workflows
- Feb 6
- Module 1LectureClinical AI Part II
- Slides, Reading List
- Feb 7
- QuizWeek 4 pre-class quiz (due Feb 12)
- Canvas
Week 4
Interpretability and explainability in biomedical AI
- Feb 13
- Module 2LectureTrustworthy AI Part I
- Slides, Reading List
- Feb 13
- QuizWeek 5 pre-class quiz (due Feb 26)
- Canvas
Week 5
Bias and fairness in biomedical AI
- Feb 27
- Module 2LectureTrustworthy AI Part II
- Slides, Reading List
- Feb 28
- QuizWeek 6 pre-class quiz (due Mar 5)
- Canvas
- Mar 1
- PSet releasedPSet 1: Bias, explainability, and fairness
- Canvas
Week 6
Foundations of geometric deep learning, graph representation learning, link prediction, node classification, graph clustering, graph classification, semi-supervised learning, label propagation, network medicine, disease modules and endotypes
- Mar 6
- Module 3LectureBiomedical graph learning Part I
- Slides, Reading List
- Mar 7
- QuizWeek 7 pre-class quiz (due Mar 12)
- Canvas
Week 7
Machine learning with heterogeneous graphs, multimodal learning, graph neural networks, knowledge graph embeddings, reasoning over knowledge graphs
- Mar 20
- Module 3LectureBiomedical graph learning Part II
- Slides - Part 1, Slides - Part 2, Reading List
- Mar 21
- QuizWeek 8 pre-class quiz (due Mar 26)
- Canvas
- Mar 22
Week 8
Foundations of natural language processing and understanding
- Mar 27
- Module 4LectureMedical language modeling Part I
- Slides, Reading List
- Mar 28
- QuizWeek 9 pre-class quiz (due Apr 2)
- Canvas
- Mar 29
Week 9
Clinical trial site identification, patient trial matching, clinical trial recruitment
- Apr 3
- Module 4LectureMedical language modeling Part II
- Slides, Reading List
- Apr 4
- QuizWeek 10 pre-class quiz (due Apr 9)
- Canvas
Week 10
Foundations of biomedical imaging, self-supervised learning, analysis of radiology images
- Apr 10
- Module 5LectureBiomedical imaging Part I
- Slides, Reading List
- Apr 11
- QuizWeek 11 pre-class quiz (due Apr 16)
- Canvas
- Apr 12
Week 11
Multimodal learning, analysis of histopathology slides, quantitative pathology in cancer diagnosis and prognosis
- Apr 17
- Module 5LectureBiomedical imaging Part II
- Slides, Reading List
- Apr 18
- QuizWeek 12 pre-class quiz (due Apr 23)
- Canvas
- Apr 19
Week 12
Overview of drug discovery and development, AI-guided drug design, small-molecule generation, molecule optimization, identification and characterization of therapeutic targets, high-throughput chemical and genetic perturbations
- Apr 24
- Module 6LectureTherapeutic science and drug discovery Part I
- Slides, Reading List
- Apr 25
- QuizWeek 13 pre-class quiz (due Apr 30)
- Canvas
Week 13
Label-efficient learning, few-shot learning, biomarker discovery, indication inference, drug repurposing, adverse event prediction
- May 1
- Module 6LectureTherapeutic science and drug discovery Part II
- Slides, Reading List
- May 2
- QuizWeek 14 pre-class quiz (due May 7)
- Canvas
- May 3
Week 14
Introduction to ethical frameworks, data privacy, regulation and liability aspects of AI