Article

Use of Noisy Labels as Weak Learners to Identify Incompletely Ascertainable Outcomes: A Feasibility Study with Opioid-Induced Respiratory Depression

2024-01-30

Abstract excerpt

<h4>Objective</h4> Assigning outcome labels to large observational data sets in a timely and accurate manner, particularly when outcomes are rare or not directly ascertainable, remains a significant challenge within biomedical informatics. We examined whether noisy labels generated from subject matter experts’ heuristics using heterogenous data types within a data programming paradigm could provide outcomes labels...

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Literature Corpus work: f45cd409-af09-53d5-8ffc-31a60cc34ff6
DOI: 10.1101/2024.01.29.24301963

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