Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge

no code implementations • 9 Apr 2021 • Prithwish Chakraborty, James Codella, Piyush Madan, Ying Li, Hu Huang, Yoonyoung Park, Chao Yan, Ziqi Zhang, Cheng Gao, Steve Nyemba, Xu Min, Sanjib Basak, Mohamed Ghalwash, Zach Shahn, Parthasararathy Suryanarayanan, Italo Buleje, Shannon Harrer, Sarah Miller, Amol Rajmane, Colin Walsh, Jonathan Wanderer, Gigi Yuen Reed, Kenney Ng, Daby Sow, Bradley A. Malin

Deep learning architectures have an extremely high-capacity for modeling complex data in a wide variety of domains.

BIG-bench Machine Learning

Question-Driven Design Process for Explainable AI User Experiences

no code implementations • 8 Apr 2021 • Q. Vera Liao, Milena Pribić, Jaesik Han, Sarah Miller, Daby Sow

A pervasive design issue of AI systems is their explainability--how to provide appropriate information to help users understand the AI.

Explainable Artificial Intelligence (XAI)

A Canonical Architecture For Predictive Analytics on Longitudinal Patient Records

no code implementations • 24 Jul 2020 • Parthasarathy Suryanarayanan, Bhavani Iyer, Prithwish Chakraborty, Bibo Hao, Italo Buleje, Piyush Madan, James Codella, Antonio Foncubierta, Divya Pathak, Sarah Miller, Amol Rajmane, Shannon Harrer, Gigi Yuan-Reed, Daby Sow

Many institutions within the healthcare ecosystem are making significant investments in AI technologies to optimize their business operations at lower cost with improved patient outcomes.

Fairness Management

Questioning the AI: Informing Design Practices for Explainable AI User Experiences

no code implementations • 8 Jan 2020 • Q. Vera Liao, Daniel Gruen, Sarah Miller

A surge of interest in explainable AI (XAI) has led to a vast collection of algorithmic work on the topic.

Explainable Artificial Intelligence (XAI) Open-Ended Question Answering