568 citations · 1.3k across the 79 of their papers we have counts for
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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…
Comparing Rule-Based and Deep Learning Models for Patient Phenotyping
Sebastian Gehrmann, Franck Dernoncourt, Yeran Li +8
Objective: We investigate whether deep learning techniques for natural language processing (NLP) can be used efficiently for patient phenotyping. Patient phenotyping is a classific…