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Found 3 papers, 1 papers with code
LATTE: Label-efficient Incident Phenotyping from Longitudinal Electronic Health Records
We propose a LAbel-efficienT incidenT phEnotyping (LATTE) algorithm to accurately annotate the timing of clinical events from longitudinal EHR data.
Unsupervised Ensemble Learning via Ising Model Approximation with Application to Phenotyping Prediction
In this paper, we propose a novel method-- unsupervised ensemble learning via Ising model approximation (unElisa) that combines a pruning step with a predicting step.
NILE: Fast Natural Language Processing for Electronic Health Records
This paper introduces the design and performance of Narrative Information Linear Extraction (NILE), a natural language processing (NLP) package for EHR analysis that we share with the medical informatics community.
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