November 24th, 2021 | 4pm-5pm, Virtual
Engineering Perspective
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.
Join us on November 24th and find your new collaborator!
Speakers
Prof. Purang Abolmaesumi
Electrical & Computer Engineering
Dr. Abolmaesumi is internationally recognized and has received numerous awards for his pioneering developments in medical image analysis and image-guided interventions. He carries out research in medical imaging, machine learning, and image-guided diagnosis and interventions. Artificial intelligence and machine learning techniques are applied to diagnosis in ultrasound, magnetic resonance imaging, digitized pathology slides and other tissue images.
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.
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.
Maryam Tayyab
Maryam is an Electrical Engineer with a background in Medical Imaging and a passion for learning new things. She's currently pursuing a Master's degree in Biomedical Engineering with a focus on developing deep learning methods to perform computer-assisted diagnosis and prediction of disease progression in Multiple Sclerosis using brain MRIs.
Hoda Hashemi
Hoda 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 Computer Vision-based algorithms for 3D tissue motion estimation and ultrafast elastography to improve the accuracy of the ultrasound image analysis and reduce the patient examination time.
Previous Workshops
Future Data Science & Health Workshop series
- November 2021 – Engineering Perspectives: Meet engineers and learn how data science, artificial intelligence, and machine learning have been used to develop solutions in the health care sphere.
- January 2022 – Clinical Perspectives: Share the clinical challenges you face and get insight on potential data science solutions from a team of engineers focused on health applications.
- January - June 2022 – 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 is available to prepare for internal and external funding opportunities in Fall 2021.