Browse Items (5 total)

Background: Assessing patient-reported outcomes (PROs) through interviews or conversations during clinical encounters provides insightful information about survivorship. Objective: This study aims to test the validity of natural language processing…

Objectives: Accurate prediction of time to death after withdrawal of life-sustaining therapies may improve counseling for families and help identify candidates for organ donation after cardiac death. The study objectives were to: 1) train a long…

Medical researchers looking for evidence pertinent to a specific clinical question must navigate an increasingly voluminous corpus of published literature. This data deluge has motivated the development of machine learning and data mining…

INTRODUCTION: Predicting time to death after terminal extubation is valuable to augment family counseling and identify suitable candidates for organ donation after circulatory death (DCD). Our objective was to train and validate a machine learning…

Accurately predicting time to death after withdrawal of life-sustaining treatment is valuable for family counseling and for identifying candidates for organ donation after cardiac death. This topic has been well studied in adults, but literature is…
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