960 citations · 3.4k across the 60 of their papers we have counts for
5 papers · 1 filter
Short-term Mortality Prediction for Elderly Patients Using Medicare Claims Data
Maggie Makar, Marzyeh Ghassemi, David Cutler +1
Risk prediction is central to both clinical medicine and public health. While many machine learning models have been developed to predict mortality, they are rarely applied in the…
Deep Reinforcement Learning for Sepsis Treatment
Aniruddh Raghu, Matthieu Komorowski, Imran Ahmed +3
Sepsis is a leading cause of mortality in intensive care units and costs hospitals billions annually. Treating a septic patient is highly challenging, because individual patients r…
Clinical Intervention Prediction and Understanding using Deep Networks
Harini Suresh, Nathan Hunt, Alistair Johnson +3
Real-time prediction of clinical interventions remains a challenge within intensive care units (ICUs). This task is complicated by data sources that are noisy, sparse, heterogeneou…
Continuous State-Space Models for Optimal Sepsis Treatment - a Deep Reinforcement Learning Approach
Aniruddh Raghu, Matthieu Komorowski, Leo Anthony Celi +2
Sepsis is a leading cause of mortality in intensive care units (ICUs) and costs hospitals billions annually. Treating a septic patient is highly challenging, because individual pat…
The Use of Autoencoders for Discovering Patient Phenotypes
Harini Suresh, Peter Szolovits, Marzyeh Ghassemi
We use autoencoders to create low-dimensional embeddings of underlying patient phenotypes that we hypothesize are a governing factor in determining how different patients will reac…