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This is further complicated by the lack of interpretability in existing methods and the difficulty of detecting interaction effects\u2014nonlinear dependencies between factors like sex, age, and disease. To address this, a novel explainable machine learning method, CellPhenoX, is developed to identify cell\u2010specific phenotypes and interaction effects linked to clinical outcomes. CellPhenoX integrates classification models, explainable artificial intelligence (AI) techniques, and a statistical framework to generate interpretable, cell\u2010specific scores to uncover condition\u2010associated cell populations. Extensive benchmarking and applications demonstrate the efficacy of CellPhenoX across diverse single\u2010cell study designs, including the dedicated and disease\u2010motivated simulations, binary disease\u2010control comparisons, and severity\u2010stratified patient cohorts. Notably, CellPhenoX identifies an activated monocyte phenotype in COVID\u201019, with expansion correlated with disease severity after adjusting for covariates and interactive effects. It also uncovers a fibroblast\u2010specific state transition gradient predicting tissue inflammation in chronic diseases, and identifies therapy\u2010induced T cell changes and biomarkers linked to the tumor microenvironment. By integrating interpretability into clinical classification, CellPhenoX offers a powerful framework for translating single\u2010cell findings into clinical impact.<\/jats:p>","DOI":"10.1002\/advs.202503289","type":"journal-article","created":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T12:52:32Z","timestamp":1758631952000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["CellPhenoX: An Explainable Machine Learning Method for Identifying Cell Phenotypes To Predict Clinical Outcomes from Single\u2010Cell Multi\u2010Omics"],"prefix":"10.1002","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0887-3319","authenticated-orcid":false,"given":"Jade","family":"Young","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics University of Colorado School of Medicine  Aurora CO USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Inamo","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics University of Colorado School of Medicine  Aurora CO USA"},{"name":"Department of Medicine Rheumatology University of Colorado School of Medicine  Aurora CO USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zachary","family":"Caterer","sequence":"additional","affiliation":[{"name":"Interdisciplinary Quantitative Biology PhD Program BioFrontiers Institute University of Colorado  Boulder CO USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Revanth","family":"Krishna","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics University of Colorado School of Medicine  Aurora CO USA"},{"name":"Department of Medicine Rheumatology University of Colorado School of Medicine  Aurora CO USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6102-2970","authenticated-orcid":false,"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics University of Colorado School of Medicine  Aurora CO USA"},{"name":"Department of Medicine Rheumatology University of Colorado School of Medicine  Aurora CO USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,9,23]]},"reference":[{"key":"e_1_2_10_1_1","doi-asserted-by":"publisher","DOI":"10.1038\/nri.2017.76"},{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-022-02104-7"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41573-023-00688-4"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.4295"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.aaq0305"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-023-03143-0"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41587-020-00803-5"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41587-021-01033-z"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41587-021-01066-4"},{"key":"e_1_2_10_10_1","first-page":"4765","volume-title":"Advances in Neural Information Processing Systems","author":"Lundberg S. 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