AI/ML Glimpses From a Cancer Research Hospital
Artificial intelligence and machine learning provide unprecedented opportunities to turn data into actionable insights, and accelerate digital transformations toward intelligent hospital operations, precision health, and personalized care across the health continuum. In 2020, Memorial Sloan Kettering Cancer Center formed the AI/ML Solutions group to accelerate our academic medical center's digital transformation. AI/ML supports our quadruple aim goals of bettering patient experience, improving health outcomes, enhancing staff experience and lowering cost of care. We leverage AI/ML to unbound our traditional model into a digitally-enabled one that drives higher growth, creates more value and impacts more lives. Applying AI/ML to the fight against cancer has been immensely promising and gratifying for our technologists. Our discussion provides glimpses of MSK's journey in a practical way. We will focus on three use cases that are in active development: 1) Machine labeling of data to scale clinical prediction models, 2) Virtual multiplex re-staining of clinical pathology slides to enable cutting-edge cancer diagnosis, and 3) next-generation employee experience for question answering. Our session will include details on each use case, as well as demonstrations of our technical work.
Learning Objectives
- Discuss how artificial intelligence and machine learning is enabling innovations in cancer research and clinical care. Identify key active use cases
- Identify challenges in scaling clinical prediction models and the transformative opportunity of machine labeling of data
- Demonstrate how advanced computer vision techniques on IHC-stained pathology images enable cutting-edge cancer diagnosis models
- Describe next-generation employee experience for question-answering
Speakers
