research
∙
07/05/2023
EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
While the general machine learning (ML) community has benefited from pub...
share
research
∙
01/09/2023
Self-Supervised Time-to-Event Modeling with Structured Medical Records
Time-to-event models (also known as survival models) are used in medicin...
research
∙
07/15/2022
Treatment Heterogeneity for Survival Outcomes
Estimation of conditional average treatment effects (CATEs) plays an ess...
research
∙
11/23/2021
RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR
Despite the routine use of electronic health record (EHR) data by radiol...
research
∙
11/15/2021
Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects
There are a number of available methods that can be used for choosing wh...
research
∙
03/17/2020
A new paradigm for accelerating clinical data science at Stanford Medicine
Stanford Medicine is building a new data platform for our academic resea...
research
∙
12/11/2019
The accuracy vs. coverage trade-off in patient-facing diagnosis models
A third of adults in America use the Internet to diagnose medical concer...
research
∙
11/16/2019
Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare
There is an emerging trend in the reinforcement learning for healthcare ...
research
∙
04/14/2018
General-purpose validation and model selection when estimating individual treatment effects
Practitioners in medicine, business, political science, and other fields...
research
∙
10/31/2017
Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset
Many decisions in healthcare, business, and other policy domains are mad...
research
∙
05/19/2017