ArticleJournal of the American Medical Informatics Association : JAMIA2023
POPDx: an automated framework for patient phenotyping across 392 246 individuals in the UK Biobank study.
Article in Journal of the American Medical Informatics Association : JAMIA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- UKB-MDRMF: a multi-disease risk and multimorbidity framework based on UK biobank data.Nature communications · 2025Article
- Genetic association studies using disease liabilities from deep neural networks.American journal of human genetics · 2025Article
- Genetic association studies using disease liabilities from deep neural networks.medRxiv : the preprint server for health sciences · 2024Article
- Advancing phenotyping through informatics innovation.Journal of the American Medical Informatics Association : JAMIA · 2023Article
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3 authors.
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Abstract
objectiveFor the UK Biobank, standardized phenotype codes are associated with patients who have been hospitalized but are missing for many patients who have been treated exclusively in an outpatient setting. We describe a method for phenotype recognition that imputes phenotype codes for all UK Biobank participants. MATERIALS AND
methodsPOPDx (Population-based Objective Phenotyping by Deep Extrapolation) is a bilinear machine learning framework for simultaneously estimating the probabilities of 1538 phenotype codes. We extracted phenotypic and health-related information of 392 246 individuals from the UK Biobank for POPDx development and evaluation. A total of 12 803 ICD-10 diagnosis codes of the patients were converted to 1538 phecodes as gold standard labels. The POPDx framework was evaluated and compared to other available methods on automated multiphenotype recognition.
resultsPOPDx can predict phenotypes that are rare or even unobserved in training. We demonstrate substantial improvement of automated multiphenotype recognition across 22 disease categories, and its application in identifying key epidemiological features associated with each phenotype.
conclusionsPOPDx helps provide well-defined cohorts for downstream studies. It is a general-purpose method that can be applied to other biobanks with diverse but incomplete data.
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