The Data Science & Health CPD course is delivered in three parts: Canvas, Zoom, and our ongoing Workshop Series
The Workshop Series is designed to build momentum in our community, and help the transition from learning about data science to doing data science. We have partnered with the Faculty of Applied Science to develop a workshop series focused on building collaborative research partnerships between clinicians and data scientists. Partner with engineers to apply what you’ve learned and move your data science project forward!
JOIN US FOR A CLINICAL PERSPECTIVES WORKSHOP
Please note: This workshop has been postponed. Please stay tuned for updates and sign up below to join our workshop mailing list and we’ll keep you posted on our rescheduled event.
Clinical Perspective
Is your study right for an AI approach? Share the clinical challenges you face and get insight on potential data science solutions from a team of engineers focused on health applications.
The workshop will include:
- Clinical challenge presentations by clinicians
- Learn what’s needed for a successful AI project: expectations from the clinician collaborator, data requirements, what kind of clinical challenge is amenable to an AI solution
- Moderated group discussion and Q&A with AI experts
Our workshop aims to provide a mutual understanding for both clinicians and engineers while building a community to actively support collaboration and matching.
Join our mailing list now!
Speakers
PRASHANT PANDEY
School of Biomedical Engineering
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.
ROHIT SINGLA
Rohit is a 3rd year MD/PhD Vanier Scholar 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.
PROF. ROGER TAM
Radiology & School of Biomedical Engineering
Dr. Tam’s research interests are centered on the application of computer vision and machine learning methods to the quantitative analysis of medical images. The Tam laboratory’s current primary research direction is the use of magnetic resonance images to improve the understanding of neurological disorders such as multiple sclerosis. In general, the projects in the Tam laboratory relate to the following topics in medical imaging: in vivo imaging, imaging biomarkers, machine learning (big data analytics for medical images and personalized medicine), imaging artifacts and their impact on quantitative analysis, computational shape modelling & morphometrics, and medical informatics & distributed medical imaging systems.
DELARAM BEHNAMI
Delaram is a 4th year PhD Candidate at the Robotics and Controls Laboratory (RCL), in the Department of Electrical and Computer Engineering. Her research involves developing artificial intelligence (AI)-based frameworks for analysis, interpretation, and enhancement of medical images of various modalities, including ultrasound, CT and MR.
Previous Workshops
Join us for an introductory AI workshop
November 30th, 2020 from 10:00am to 11:30am, Online
This workshop will cover the basics of AI and its potential and limitations to address clinical problems. We'll cover necessary inputs and feasible outcomes, while clarifying what AI can and can't do. You'll leave this workshop with an understanding of AI's capabilities and limitations and what's required to collaborate on an AI project.
The workshop will include:
- An introduction to AI - review the basics
- Case studies of successful projects between clinicians and engineers
- An opportunity to engage with AI experts to evaluate potential projects
Our workshop aims to provide a mutual understanding for both clinicians and engineers, while building a community to actively support collaboration and matching.
Future Data Science & Health Workshop series
- January – June 2021 – Monthly Workshops: Clinicians will be matched with engineers to develop data science solutions to health care challenges. Monthly meetings with mentors and peers will help keep projects on track, enable knowledge sharing, and build collaborative links between our health care and engineering communities. Grant development support available to prepare for internal and external funding opportunities in Fall 2021.