Trainee Rounds: Armaan Malhotra and Yu Shi
DATE: May 28, 2024 (Tue.)
TIME: 12pm to 1pm ET
METHOD: Zoom
PRESENTERS: Armaan Malhotra and Yu Shi
Armaan Malhotra
PhD candidate, Division of Neurosurgery, Department of Surgery, University of Toronto
TITLE: An Early Warning System for the Real-time Image-Based Triage of Patients Suffering Traumatic Brain Injury: Development of ASIST-TBI
ABSTRACT: The following project will describe the development and internal validation of the Automated Surgical Intervention Support Tool for Traumatic Brain Injury (ASIST-TBI).
ABOUT: Armaan Malhotra is a 4th year neurosurgery resident and 2nd year PhD student focused on machine learning and health services to understand and improve neurotrauma outcomes.
Yu Shi
PhD candidate, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto
TITLE: Predicting a cancer dependency map of cancer patients with unsupervised deep domain adaptation
ABSTRACT: Cancer dependency maps are critical in pinpointing genes that are essential for the growth of cancer cells, setting the stage for developing targeted therapies. We present a machine learning algorithm that employs deep unsupervised domain adaptation to effectively align feature distributions across diverse data domains. Trained on labeled cancer cell line (CCL) data and validated against unseen CCL and unlabeled cancer patient data from The Cancer Genome Atlas (TCGA), our model predicts cancer patient dependency maps with better accuracy than compared baselines. This unsupervised method accurately predicts cancer dependencies in patient-derived tumors, showcasing advancements in out-of-distribution generalization for therapeutic developments.
ABOUT: Yu Shi is a second-year PhD student in Biostatistics at the University of Toronto. Prior to this, she received an MSc in Biostatistics from Yale University. Her research focuses on developing and applying advanced machine learning and statistical techniques to address challenges related to out-of-distribution data with their applications to health research. Outside of her academic endeavours, Yu Shi finds relaxation and enjoyment in playing pool and engaging in poker games.
