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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.

Marinka Zitnik

marinka@hms.harvard.edu

Office Hours: Mo, 3pm - 4pm


Week 1

Course overview and introduction to biomedical AI

Jan 23
LectureWhat makes biomedical problems unique
Slides, Reading List
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
PSet duePSet 1: Bias, explainability, and fairness
Canvas

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
PSet releasedPSet 2: Biomedical networks and graph embeddings
Canvas

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
PSet duePSet 2: Biomedical networks and graph embeddings
Canvas

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
PSet releasedPSet 3: Biomedical imaging methods and applications
Canvas

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
PSet duePSet 3: Biomedical imaging methods and applications
Canvas

Week 14

Introduction to ethical frameworks, data privacy, regulation and liability aspects of AI

May 8
LectureEthical and legal considerations for biomedical AI
Slides, Reading List