An online tool for correcting verification bias when validating electronic phenotyping algorithms

Abstract excerpt

Computable or electronic phenotypes of patient conditions are becoming more commonplace in quality improvement and clinical research. During phenotyping algorithm validation, standard classification performance measures (i.e., sensitivity, specificity, positive predictive value, negative predictive value, and accuracy) are commonly employed. When validation is performed on a randomly sampled patient population, di...

Topics

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• Biomedical Research
• Algorithms
• Computer Communication Networks
• Electronic Health Records
• Machine Learning
• Natural Language Processing
• Phenotype
• Reference Standards

Identifiers and source

Literature Corpus work

84f8a78f-de1e-5f5b-9eb9-144dd4f75952

DOI

10.1101/2023.11.22.23298913