BME 5310

BME 5310

Course information provided by the Courses of Study 2020-2021.

Course provides a theoretical foundation for advanced machine learning methods applicable to the analysis of large-scale biomedical data. These applications often have two distinct goals: (1) computation of predictions, and (2) understanding underlying biological mechanisms. A range of examples will be included that cover various data modalities (e.g., DNA sequence data, electronic health record data, images) and different goals. There will be a class project that will involve identifying a data-set, selection of appropriate machine learning problem, writing code and conducting analyses, an oral presentation of results and a written report.

When Offered Fall.

Prerequisites/Corequisites Prerequisite: MATH 2940 or equivalent, BTRY 3010 or CEE 3040, or permission of instructor. Recommended prerequisite: CS 1110 or CS 1112 or equivalent.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Combined with: ECE 5970

  • 3 Credits Graded

  • 17642 BME 5310   LEC 001

  • Instruction Mode: In Person Transition to Online
    Enrollment limited to students who are able to attend in-person classes in the Ithaca area.

Syllabi: none
  •   Regular Academic Session.  Combined with: ECE 5970

  • 3 Credits Graded

  • 21251 BME 5310   LEC 002

    • TR Online Meeting
    • Sep 2 - Dec 16, 2020
    • Sabuncu, M

  • Instruction Mode: Online