MMCI 517 APPLIED DATA SCIENCE

May 5, 2023

Course Overview

517 Applied Data Science Syllabus 2023  https://ja.dh.duke.edu/system/files/517%20Applied%20Data%20Science%20Syllabus%202023_0.docx

Data science and machine learning are now beginning to impact clinical medicine, with performance on some tasks, such as detection of skin cancer, exceeding that of experienced clinicians. This course is designed to introduce students to the data science techniques poised to disrupt clinical practice through foundational material and clinical case studies. Course content will provide students with an intuitive, applications-oriented foundation in these techniques while highlighting both their capabilities and current limitations. Students will be introduced to pitfalls commonly encountered when developing models for clinical data as well as relevant practical and ethical considerations.

The course will emphasize the following areas:

  • Introduction to the multilayer perceptron, with applications to EHR predictive modeling
  • Convolutional neural networks for medical image analysis
  • Natural language processing for patient notes and other text data
  • Methods and models for clinical time-series
  • Reinforcement learning for sequential clinical decision-making

It will culminate in a final design project in which students will work in their teams to propose a novel data science project related to a clinical topic of their interest. Projects will focus on one of the data science areas listed above and detail the proposed approach to data collection or extraction, model development, and model validation.

Target Audience

  • Physicians

Learning Objectives

Course Objective

To provide students with an understanding of the capabilities and limitations of healthcare data science sufficient:

  1. Design and manage research projects in this area.
  2. Collaborate and communicate effectively with data scientists and data science researchers.

  3. Critically evaluate data science methodology, with an emphasis on model validation. Students will be exposed to the material through lectures, hands-on group exercises, written exercises drawing from the scientific literature, and a final project in data science research design.

 

Course summary
Available credit: 
  • 2.50 AMA PRA Category 1 Credit(s)™
  • 2.50 Attendance
  • 2.50 JA Credit - AH
Registration Opens: 
05/05/2023
Registration Expires: 
05/05/2025
Activity Starts: 
05/05/2023 - 8:00am EDT
Activity Ends: 
05/05/2023 - 10:30am EDT
Add to calendar: 
Rating: 
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NC 27705
United States

Disclosure Statement

Duke University Health System Department of Clinical Education and Professional Development adheres to ACCME Essential Areas and Policies regarding industry support of continuing medical education. Disclosures of faculty/planning committee members and commercial relationships will be made known at the activity. Speakers are also expected to openly disclose a discussion of any off-label, experimental, or investigational use of drugs or devices in their presentations.

 

Disclosure link: 
Continuing Education Disclosure Form

Credit Statement

Duke University Health System Department of Clinical Education and Professional Development designates this live activity for a maximum of (2.50 ) AMA PRA Category 1 Credit(s) .

Physicians should claim only credit commensurate with the extent of their participation in the activity.

Accreditation In support of improving patient In support of improving patient care, the Duke University Health System Department of Clinical Education and Professional Development is accredited by the American Nurses Credentialing Center (ANCC), the Accreditation Council for Pharmacy Education (ACPE), and the Accreditation Council for Continuing Medical Education (ACCME), to provide continuing education for the health care team

Available Credit

  • 2.50 AMA PRA Category 1 Credit(s)™
  • 2.50 Attendance
  • 2.50 JA Credit - AH
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