PHM5005 – AI and Machine Learning for Precision Medicine

Course Overview

The convergence of Artificial Intelligence (AI) and precision medicine is poised to transform healthcare in the coming years. This course aims to introduce fundamental knowledge and skills in the application of Artificial Intelligence/Machine Learning (AI/ML) in Precision Medicine. This course will allow students to develop the skills to pre-process and analyse data using AI/ML techniques, generate insights, as well as build and explain predictive models for precision medicine.

Learning Outcomes

At the end of this course, students should be able to

  • Explain applications of AI/ML in precision medicine
  • Evaluate the different approaches of AI/ML and their suitability for the analysis of data for precision medicine
  • Evaluate data quality and perform appropriate pre-processing for AI/ML of precision medicine data
  • Perform unsupervised learning of precision medicine data for pattern discovery
  • Perform supervised learning of precision medicine data to build and/or use a predictive model
  • Evaluate the performance and explainability of a predictive model

Course Outline

  • Overview of AI/ML applications in precision medicine
  • Approaches for AL/ML in precision medicine 
  • Unsupervised learning for pattern discovery
  • Supervised learning for predictive modeling
  • Evaluation of predictive models
  • Explainability of predictive models

    Course Requirements

    Familiarity with Python and/or R

    Course Coordinators

    Dr Kenneth Ban

    Programme Director, National Supercomputing Cluster Singapore (NSCC)

    Senior Lecturer, Dept of Biochemistry, NUS
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    Dr Lee Hwee Kuan

    Head of Research Division, Bioinformatics Institute, A*STAR

    Adjunct Assoc Prof, Dept of Computer Science, NUS
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