Principal Investigator Pavel Etingof
Marzyeh Ghassemi Associate Professor, MIT Department of Electrical Engineering and Computer Science (EECS) and Institute for Medical Engineering & Science (IMES)
Machine learning in health has made impressive progress in recent years, powered by an increasing availability of health-related data and high-capacity models. While many models in health now perform at, or above, humans in a range of tasks across the human lifespan, models also learn societal biases and may replicate or expand them. In this talk, Dr. Marzyeh Ghassemi will focus on the need for machine learning researchers and model developers to create robust models that can be ethically deployed in health settings, and beyond. Dr. Ghassemi's talk will span issues in data collection, outcome definition, algorithm development, and deployment considerations.
Principal Investigator Polina Golland
Moderator: John Roberts Panelists: - Ellie Chabi, Santen Pharmaceutical - Ryan Davis, Secure AI Labs - Prof. Martha Gray, MIT - Cory Kidd, Catalia Health - Andrew A. Radin, twoXAR
In response to new business models, accelerated timelines, and unforeseen market dynamics, healthcare companies are seeking to innovate rapidly and effectively to meet new challenges. A key criterion for success is the adoption of cutting-edge tools that derisk and accelerate the drug development process. Investment in these tools pays dividends across a company's pipeline.
Learn about the challenges faced by the industry and the potential solutions and technologies that are made available by MIT researchers.
Paula Hammond Head, Department of Chemical Engineering; David H. Koch Professor of Chemical Engineering