ArticleBiomedical engineering and computational biology2019
Extending Classification Algorithms to Case-Control Studies.
Article in Biomedical engineering and computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Personal and environmental predictors of polycyclic aromatic hydrocarbon exposure identified through repeated silicone wristband sampling.Environmental pollution (Barking, Essex : 1987) · 2026Article
- Pre-diagnostic serum metabolome and breast cancer risk: a nested case-control study.Breast cancer research : BCR · 2025Article
- RNA sequencing identifiesCytotechnology · 2025Article
- PEDI: Towards Efficient Pathway Enrichment and Data Integration in Bioinformatics for Healthcare Using Deep Learning Optimisation.Biomedical engineering and computational biology · 2025Article
- Robust Cancer Biomarker Identification From Matched Transcriptomic Data Via Bootstrapped Regularized Conditional Logistic Regression.Cancer informatics · 2025Article
- Machine learning models based on fluid immunoproteins that predict non-AIDS adverse events in people with HIV.iScience · 2024Article
- The predictive power of data: machine learning analysis for Covid-19 mortality based on personal, clinical, preclinical, and laboratory variables in a case-control study.BMC infectious diseases · 2024Article
- Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity.Cell reports. Medicine · 2023Article
- EPIMUTESTR: a nearest neighbor machine learning approach to predict cancer driver genes from the evolutionary action of coding variants.Nucleic acids research · 2022Article
- Prediction of Type 1 Diabetes at Birth: Cord Blood Metabolites vs Genetic Risk Score in the Norwegian Mother, Father, and Child Cohort.The Journal of clinical endocrinology and metabolism · 2021Article
- Lipid Profiles and Heart Failure Risk: Results From Two Prospective Studies.Circulation research · 2021Article
- Prediction of the development of islet autoantibodies through integration of environmental, genetic, and metabolic markers.Journal of diabetes · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Classification is a common technique applied to 'omics data to build predictive models and identify potential markers of biomedical outcomes. Despite the prevalence of case-control studies, the number of classification methods available to analyze data generated by such studies is extremely limited. Conditional logistic regression is the most commonly used technique, but the associated modeling assumptions limit its ability to identify a large class of sufficiently complicated 'omic signatures. We propose a data preprocessing step which generalizes and makes any linear or nonlinear classification algorithm, even those typically not appropriate for matched design data, available to be used to model case-control data and identify relevant biomarkers in these study designs. We demonstrate on simulated case-control data that both the classification and variable selection accuracy of each method is improved after applying this processing step and that the proposed methods are comparable to or outperform existing variable selection methods. Finally, we demonstrate the impact of conditional classification algorithms on a large cohort study of children with islet autoimmunity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.