#336546

Machine Learning in Healthcare

Syllabus    Notations

Instructor

Joachim Behar

Teaching Assistants

  • Moran Davoodi
  • Yuval Ben Sason
  • Kevin Kotzen

#336546

Machine Learning in Healthcare

Syllabus    Notations

Instructor

Joachim Behar

Teaching Assistants

Moran Davoodi
Yuval Ben Sason
Kevin Kotzen

Summary

In this course you will learn about aspects of information processing including data preprocessing, visualization, regression, dimensionality reduction (PCA, ICA), feature selection, classification (LR, SVM, NN) and their usage for decision support in the context of healthcare. The course aims to provide an overview of computer tools and machine learning techniques for dealing with medical datasets (time series and images). The course is practical with computer based tutorials and assignments. The necessary theory will be covered.

Logistics

Teaching Objectives

Students will acquire the following skills

  • Python for biomedical data science
  • Main classifiers, intuition and mathematical background
  • Neural networks and deep learning
  • Performance statistics in healthcare
  • ML for diagnosis, prognosis and treatment

Course Material

The course material can also be found at our public Github repository

Course Staff

  • Joachim Behar, PhD

  • Moran Davoodi
    PhD candidate

  • Yuval Ben Sason
    MSc candidate

  • Kevin Kotzen
    MSc candidate

  • Anne Weill, PhD
    Technion, BME

  • Danny Eytan, MD-PhD
    Rambam Hospital