Multi-Label Learning

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Predicting emergency department orders with multilabel machine learning techniques and simulating effects on length of stay

Emergency departments (EDs) continue to pursue optimal patient flow without sacrificing quality of care. The speed with which a healthcare provider receives pertinent information, such as results from clinical orders, can impact flow. We seek to determine if clinical ordering behavior can be predicted at triage during an ED visit.

10p visteverogers 24-06-2023 4 2 Download

Cohort selection for clinical trials using deep learning models

The goal of the 2018 n2c2 shared task on cohort selection for clinical trials (track 1) is to identify which patients meet the selection criteria for clinical trials. Cohort selection is a particularly demanding task to which natural language processing and deep learning can make a valuable contribution. Our goal is to evaluate several deep learning architectures to deal with this task.

8p visteverogers 24-06-2023 8 2 Download