Machine Learning for Healthcare

MACHN LEARNING HEALTHCARE

Prerequisites: Medical Informatics G4001, Computer Science W3139. Survey of the methods underlying the field of medical informatics. Explores techniques in mathematics, logic, decision science, computer science, engineering, cognitive science, management science and epidemiology, and demonstrates the application to health care and biomedicine.

• F 10:30 a.m.-11:45 a.m.
• Instructor: Shalmali Joshi
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• 3 points

ACCULTURATN TO MED & CLIN INFO

Overview of the field of medicine for informaticians. Medical language and terminology, introduction to pathology and pathophysiology, the process of medical decision making, and an understanding of how information flows in the practice of medicine.

• T 2:30 p.m.-5 p.m.
• Instructor: Sivan Kinberg
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• 3 points

MTHDS IN HLTH INFORMATION TECH

• F 9 a.m.-1 p.m.
• Instructor: Virginia G Lorenzi
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• 3 points

BIOLOGICAL SEQUENCE ANALYSIS

• W 9 a.m.-noon
• Instructor: Richard A Friedman
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• 3 points

HEALTH INFO TECHNOLOGY

SKILLS & MTHDS IN HIT

• F 1:10 p.m.-5 p.m.
• Instructor: Virginia G Lorenzi
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• 3 points

Computational Epidemiology

This course delves into the intersection of epidemiology and computational methods, equipping students with the tools to conduct rigorous epidemiological studies from big clinical data repositories. Students will explore techniques from informatics, computer science, machine learning, and statistics to clean, analyze, and interpret data from electronic health records (EHRs) and other large-scale datasets. Through hands-on projects and case students, students will gain practical experience in applying epidemiologic study designs to uncover patterns, identify risk factors, model disease transmission dynamics, and evaluate interventions. This interdisciplinary approach prepares students to address real-world public health challenges by leveraging the power of data-driven insights. The course is broken up into modules, each of which covers an epidemiologic study design or principle. Modules will range from 1-3 classes, and will include (i) a lecture and (ii) accompanying lab work. Students are expected to read technical texts carefully, participate actively in lecture discussion, and develop hands-on skills in labs involving real-world biomedical and health datasets. Students will curate their own analytic datasets from Observational Health Data Sciences and Informatics (OHDSI)-formatted electronic health record (SynPUF) data.

• MW 2 p.m.-3:30 p.m.
• Instructor: Amelia J Averitt
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• 3 points

RES SEM IN BIOMED INFORMATICS

Prerequisite: open to public. Presentations by medical informatics faculty and invited international speakers in medical informatics, computer science, nursing informatics, library science, and related fields.

• M 1 p.m.-2 p.m.
• Instructor: Sarah A Rossetti
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• 1 points

PROJECTS-BIOMEDICAL INFORMATCS

Research in medical informatics under the direction of a faculty adviser.

• Instructor: Noemie Elhadad
  Wikipedia h-index: 46 Info
• Instructor: Chunhua Weng
  h-index: 37 Info
• Instructor: Harris Wang
  h-index: 32 Info
• Instructor: Andrea Califano
  h-index: 77 Info
• Instructor: Dennis Vitkup
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• Instructor: Raul Rabadan
  Wikipedia h-index: 72 Info
• Instructor: Rita Kukafka
  h-index: 28 Info
• Instructor: George M Hripcsak
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• Instructor: Pierre Elias
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• Instructor: Herbert S Jr Chase
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• Instructor: Olena Mamykina
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• Instructor: Yufeng Shen
  h-index: 47 Info
• Instructor: Nicholas Tatonetti
  Wikipedia h-index: 36 Info
• Instructor: Karthik Natarajan
  h-index: 17 Info
• Instructor: Gamze Gursoy
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• Instructor: Sarah A Rossetti
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• Instructor: Patrick B Ryan
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• Instructor: Richard A Friedman
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• 1-12 points

PROJECTS-BIOMEDICAL INFORMATCS

Research in medical informatics under the direction of a faculty adviser.

• Instructor: Mohammed Alquraishi
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• Instructor: Tal Korem
  h-index: 18 Info
• Instructor: Shalmali Joshi
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• Instructor: Jason Adelman
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• 1-12 points

METHODS III: RESEARCH METHODS

• F 9 a.m.-10:15 a.m.
• Instructor: Olena Mamykina
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• 3 points

M.PHIL TEACHING EXPERIENCE

Prerequisite: instructors permission. Participation in medical informatics educational activities under the direction of a faculty adviser.

• Instructor: Shalmali Joshi
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• Instructor: Richard A Friedman
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• Instructor: Olena Mamykina
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• Instructor: Sivan Kinberg
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• 2 points

DOCTORAL RESEARCH

Prerequisite: completion of all M.Phil. requirements, and approval of a research proposal by the supervising faculty adviser.

• Instructor: Noemie Elhadad
  Wikipedia h-index: 46 Info
• Instructor: Chunhua Weng
  h-index: 37 Info
• Instructor: Dennis Vitkup
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• Instructor: Raul Rabadan
  Wikipedia h-index: 72 Info
• Instructor: Olena Mamykina
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• Instructor: Sarah A Rossetti
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• Instructor: George M Hripcsak
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• Instructor: Gamze Gursoy
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• Instructor: Harris Wang
  h-index: 32 Info
• 1-12 points

DOCTORAL DISSERTATION

Prerequisite: completion of all M.Phil. requirements. Ph.D. candidates may be required to register for this course every term during the preparation of the dissertation.

• Instructor: Olena Mamykina
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• Instructor: Noemie Elhadad
  Wikipedia h-index: 46 Info
• Instructor: Dennis Vitkup
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• Instructor: Nicholas Tatonetti
  Wikipedia h-index: 36 Info
• Instructor: George M Hripcsak
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• Instructor: Harris Wang
  h-index: 32 Info
• Instructor: Gamze Gursoy
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• 0 points