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From the 1 of 7 linked papers with an AI index.

activity
20172020
most citedSynth-Validation: Selecting the Best Causal Inference Method for a Given Dataset

8 citations · 8 across the 2 of their papers we have counts for

collaborators

7 papers

cs.CL2020

Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data

Ethan Steinberg, Ken Jung, Jason A. Fries +3

Widespread adoption of electronic health records (EHRs) has fueled the development of using machine learning to build prediction models for various clinical outcomes. This process…

cs.LG2018

Predicting Inpatient Discharge Prioritization With Electronic Health Records

Anand Avati, Stephen Pfohl, Chris Lin +7

The paper develops machine‑learning models using eight years of Stanford Hospital electronic health records to predict which inpatients will be discharged within the next 24 hours,…

stat.ML2018

The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data

Daisy Yi Ding, Chloé Simpson, Stephen Pfohl +3

Electronic phenotyping is the task of ascertaining whether an individual has a medical condition of interest by analyzing their medical record and is foundational in clinical infor…

cs.LG2018

Countdown Regression: Sharp and Calibrated Survival Predictions

Anand Avati, Tony Duan, Sharon Zhou +3

Probabilistic survival predictions from models trained with Maximum Likelihood Estimation (MLE) can have high, and sometimes unacceptably high variance. The field of meteorology, w…

cs.CY2017

Improving Palliative Care with Deep Learning

Anand Avati, Kenneth Jung, Stephanie Harman +3

Improving the quality of end-of-life care for hospitalized patients is a priority for healthcare organizations. Studies have shown that physicians tend to over-estimate prognoses,…

stat.ML20178 cited

Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset

Alejandro Schuler, Ken Jung, Robert Tibshirani +2

Many decisions in healthcare, business, and other policy domains are made without the support of rigorous evidence due to the cost and complexity of performing randomized experimen…