Transforming Decision Making in Medical Interventions Using Innovations in AI

Dr. Parvin Mousavi’s research integrates computing science and engineering to translate cutting-edge AI advancements into practical applications that improve disease diagnosis, medical interventions, and personalized treatments. Her multidisciplinary approach spans machine learning, medical imaging, computer-assisted interventions, computational biology, and bioinformatics, aiming to uncover new insights from biological data that enhance clinical outcomes. As the Canada Research Chair in Medical Informatics, Dr. Mousavi’s work is at the forefront of developing robust machine learning methods tailored for the unique demands of healthcare, ensuring that AI technologies can be effectively integrated into medical practice.

Decision making based on digital technology and machine learning is only reasonable with abundant, high-quality data. While millions of data points can now be stored from images, signals and text during interventions, they are often noisy and sparsely labeled, lacking the high-fidelity, one-to-one correspondence required to build accurate machine learning solutions. Innovations in machine learning are required to overcome these challenges, enabling interpretable and actionable insights. The objective is to fundamentally change disease diagnosis, interventions, and identification of optimized and tailored treatments for individual patients, disrupting how clinical information is thought of and transforming clinical decision making. Dr. Mousavi’s research is in partnership with industry and health institutions and contributes to the critical dialogue surrounding societal impacts of AI through health and wellbeing for all.