Artificial Intelligence for Medical Students
The 2021 workshop will be held Mar 2, 16, 23, and April 6 at 6-7PM Pacific. Click here to join!
Join our Slack channel here for discussions and announcements as well!
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.
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).
Ricky is a 2nd year medical student at Queen's University. He completed a MASc in Biomedical Engineering at UBC, building machine learning methods for classification of fetal ultrasound images. He completed a BASc in Engineering Physics and Mathematics at UBC.
Prashant is a PhD Vanier Scholar in Biomedical Engineering at UBC, working on ultrasound-based orthopaedic surgical navigation with machine learning. He previously completed a MASc developing real-time ultrasound bone segmentation for pelvic fractures.
Zoe is a 3rd year medical student at Queen's University, with research work in 3D segmentation of ultrasound images with machine learning. Zoe completed a BSc in computer science at McGill and worked as a software engineering intern at Quora and Facebook.
Olivia is a 2nd year medical student at UBC, previously completing a MSc in experimental medicine at Queen's University. She has worked in developing novel echocardiography contrast methods for atherosclerosis therapy.
Rohit is a 3rd year MD/PhD at UBC, working on automated anlaysis of renal ultrasound in his PhD. He previously completed a MASc in Biomedical Engineering at UBC with work in developing augmented reality for surgical guidance.
Kevin is a 4th year medical student at UBC, who has pioneered the AI in Medicine club and the AI for Medical Students workshop in 2019.
Patrick Wang is a third year medical student at Queen's University. His interest in AI started in his first year after being involved in various research projects related to ophthalmology imaging. Before medical school, Patrick studied Health Sciences at McMaster University for three years. In his free time, he enjoys cooking and photography.
Minnie is a 1st year medical student at UBC. She previously completed a BSc and MScOT at UBC and worked as a data science fellow with the BCCDC to forecast wildfire smoke.