Trainee Rounds: Lianghong Chen and Timur Latypov
DATE: June 11 (Tue.)
TIME: 12pm to 1pm ET
METHOD: Zoom
PRESENTERS: Lianghong Chen and Timur Latypov
Lianghong Chen
Master's student, Department of Computer Science, Western University
TITLE: Conditional Probabilistic Diffusion Model Driven Synthetic Radiogenomic Applications in Breast Cancer
ABSTRACT: Lianghong’s research presents an innovative approach that merges radiogenomics with novel deep-learning techniques to advance precision oncology in the field of breast cancer. He used a conditional probabilistic diffusion model to generate magnetic resonance images for patients in the database with only multi or single-omic data. The synthetic images were further evaluated for potential breast cancer clinical applications, such as predicting Estrogen Receptor (ER) status, and ER-positive/Human Epidermal Growth Factor Receptor 2-positive (ER+/Her2+) subtypes. His study contributes novel insights into the emerging field of radiogenomics and can empower future machine learning-driven breast cancer precision medicine.
ABOUT: Lianghong Chen is a Master’s student in Computer Science at Western University under the supervision of Dr. Pingzhao Hu and Dr. Mike Domaratzki, specializing in deep learning and reinforcement learning. Having earned a Bachelor of Science in Computer Science from the same institution, Lianghong has been honored with the prestigious Vector Institute Scholarships in Artificial Intelligence. Actively involved in various AI for health research initiatives, Lianghong has made significant contributions to the works submitted to prestigious conferences and journals. With a goal to pursue a Ph.D. in Artificial Intelligence for health, Lianghong aspires to contribute to cutting-edge research and advancements in technology.
Timur Latypov
PhD candidate, Institute of Medical Science, University of Toronto
TITLE: Signatures of Chronic Facial Pain: Interfacing Artificial intelligence and multimodal brain imaging
ABSTRACT: Chronic pain, particularly Trigeminal Neuralgia (TN), poses a significant global health challenge. Our research bridges the gap in uncovering changes in the brain in chronic pain by interfacing artificial intelligence (AI) with MRI and clinical data. Using this approach we identified structural imaging signatures distinct for TN and TN secondary to multiple sclerosis, were able to predict outcomes of surgical treatment of TN using pre-surgical data and identified factors that determine how well this condition can be treated. Our work enhances our grasp of TN's complex neurological changes and promises to improve assessment strategies for TN and chronic pain.
AFFILIATIONS: (1) Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto; (2) Krembil Research Institute, University Health Network
ABOUT: Dr. Timur Latypov is currently pursuing his PhD at the University of Toronto's Institute of Medical Science, under the mentorship of Dr. Mojgan Hodaie. Before joining the PhD program, Dr. Latypov earned his Doctor of Medicine degree from Kazan Federal University (Russia). His research is at the intersection of artificial intelligence (AI), healthcare, and neuroscience. Specifically, his PhD project is dedicated to investigating the brain imaging signatures associated with chronic facial pain syndromes through the use of advanced AI techniques
