INFO 5375: Health Tech Oriented Machine Learning

Jan 24-May 10 – Mondays and Wednesdays 9:40—10:55 A.M.

Instructor: Fei Wang (few2001@med.cornell.edu)

Course Objective: This course introduces students the various types of health data, including patient clinical records, medical images, physiological and vital signals from wearable sensors, multi-omics, etc. and how to use machine learning algorithms to analyze these data and help with real world health problems such as patient screening, risk modeling, disease subtyping and precision medicine. The technical topics to be introduced in this class include classic supervised and unsupervised learning, network analysis, probabilistic modeling, deep learning, transfer learning, algorithmic fairness and interpretability. We will also invite clinicians or researchers working in the health industry to deliver guest lecturers in the class. The students will gain hands-on experience on analyzing real world health data during course assignments and projects.

Credits: 3 credits.

Teaching Assistants: Dan Adler (daa243@cornell.edu) and Zilong Bai (zib4001@med.cornell.edu).

Course Format:
  • 75 minutes lectures twice a week (including guest lectures)
  • 3 programming assignments
  • 1 final project (in groups, 2-3 students per group)

    • Prerequisites: Machine Learning, Python Programming

    Date Content Presenter Materials Assignments
    01/24/2022 Introduction of machine learning and healthcare Fei Wang    
    01/26/2022 Overview of healthcare data and machine learning strategies Fei Wang    
    01/31/2022 Predictive Modeling with Electronic Health Records Zhenxing Xu   Assignment 1 Posted
    02/02/2022 Predictive Modeling with Mobile Sensing Data Dan Adler    
    02/07/2022 Predictive Modeling with Multi-Modal Health Data Benjamin Glicksberg    
    02/09/2022 Disease Subphenotyping with Electronic Health Records Chang Su    
    02/14/2022 Longitudinal Disease Subphenotyping with Electronic Health Records Hao Zhang    
    02/16/2022 Machine Learning for Critical Care Edward Schenck    
    02/21/2022 Evaluating Machine Learning for Real-World Implemetation Yiye Zhang    
    02/23/2022 Medical Image Analysis using Multi-Modal Data Yingying Zhu   Assignment 1 Due, Assignment 2 Posted
    03/02/2022 Machine Learning for Alzheimer's Disease Jiayu Zhou    
    03/07/2022 Computational Pathology Matthew Brendel    
    03/09/2022 Machine Learning for Rheumatology Richard Bell    
    03/14/2022 Mid-term Course Review Fei Wang   Assignment 2 Due
    03/16/2022 Clinical Natural Language Processing I Yifan Peng    
    03/21/2022 Canceled Canceled   Final Project Proposal Due, Assignment 3 Posted
    03/23/2022 Biomedical Ontologies Licong Cui    
    03/28/2022 Clinical Natural Language Processing II Yanshan Wang    
    03/30/2022 Biomedical Knowledge Graph Rui Zhang    
    04/11/2022 Machine Learning for Multi-Omics Analysis Yue Li    
    04/13/2022 Graph Learning for Pharmaceutical Research and Design Fei Wang    
    04/18/2022 High-Throughput Trial Emulation with Real World Data Chengxi Zang   Assignment 3 Due
    04/20/2022 TBD Yuan Luo    
    04/25/2022 Algorithmic Bias Fei Wang    
    04/27/2022 ML for COVID-19 I Fei Wang    
    05/02/2022 ML for COVID-19 II Fei Wang    
    05/04/2022 Project Presentations Student Teams    
    05/09/2022 Class Wrap-up Fei Wang   Final Project Report Due

    © Fei Wang