We hosted the 5th iteration of our workshop series in spring 2023 with over 200 cumulative attendees! You can guide yourself through our updated slides and videos below. Information about upcoming events will be posted here.
Artifical intelligence and computer-aided anlaysis have been progressing rapidly, with many potential applications to address clinical problems. This course aims to introduce key AI concepts to medical students to be comfortable in engaging with AI in their clinical careers. No technical background is required.
Workshop Slides, Recordings and Code:
Session 1 Recording: Intro to AI, Definitions, Misconceptions
Session 1 CoLab Code: Exploratory Data Analysis
Session 2 Slides: Data Science and Preprocessing
Session 2 Recording: Data Science and Preprocessing
Session 2 CoLab Code: PCA, and Clustering, and Logistic Regression
Session 3 Slides: Machine Learning Models
Session 3 Recording: Machine Learning Models
Session 3 CoLab Code: Decision Trees and Cross-Validation
This course includes:
Tutorials from AI Engineers
5 1-hour workshops introducing core topics and applications to medicine, including categorical ideas (machine learning, classification, computer vision, supervised/unsupervised learning) and methods (kNN, random forests, neural networks, deep learning, convolutional neural networks).
Guided Programming Project
Instructing how to set up a Python AI program to develop decision trees, a common method in journal papers, emphasizing on data processing - a common task requiring expertise of medical students and residents.
Training to Evaluate AI Applications
Providing enough context to students such that they can assess the capabilities and limitations of AI in a specific project.
Interaction with AI Researchers
Providing the opportunity for students to engage with AI experts to answer and evaluate any questions they have related to AI in their clinical career (photo of some participants in the 2019 workshop).