Press
Alzheimer's disease therapeutic target
Alzheimer's disease therapeutic target
- Our EMBARKER project on identifying therapeutic targets for Alzheimer's disease won the Madrona Prize at the Allen School 2018 Industry Affiliates Annual Research Day.
- GeekWire - From fighting Alzheimer’s to AR captions, UW computer science students show cutting-edge innovations
- BusinessWire - Madrona Awards 2018 Madrona Prize to UW Project That Applies Machine Learning to Fighting Alzheimer’s Disease
Prescience
Prescience
Scott M. Lundberg, Bala Nair, Monica S. Vavilala, Mayumi Horibe, Michael J. Eisses, Trevor Adams, David E. Liston, Daniel King-Wai Low, Shu-Fang Newman, Jerry Kim, and Su-In Lee*. Explainable machine learning predictions to help anesthesiologists prevent hypoxemia during surgery. [Paper] Nature BME 2, 749–760 (2018) - Featured on the Cover
- Nature BME Editorial - Towards trustable machine learning
- UW News - Prescience: Helping doctors predict the future
- GeekWire - Univ. of Washington researchers unveil Prescience, an AI system that predicts problems during surgery
- Allen School News - “Prescience” interpretable machine-learning system for predicting complications during surgery featured in Nature Biomedical Engineering
Cancer precision medicine
Cancer precision medicine
- GeekWire - Using precision medicine to kill cancer — with artificial intelligence
- Allen School News - Researchers “MERGE” machine learning and medicine to enable targeted treatment of individual cancer patients
- UW Huddle - Personal beginnings for a personalized medicine breakthrough
- 1 year, 10 innovations from UW's Paul G. Allen School of CSE
Alzheimer's disease therapeutic target
Alzheimer's disease therapeutic target
- Big data framework seeks treatment targets for Alzheimer’s disease
- What really causes Alzheimer's and how might we fix it?
Others
Others