{"doi":"10.1093/biomtc/ujaf021","title":"Sparse Bernoulli mixture modeling with negative-unlabeled data: an approach to identify and characterize long COVID","abstract":"SARS-CoV-2-infected individuals have reported a diverse collection of persistent and often debilitating symptoms commonly referred to as long COVID or post-acute sequelae of SARS-CoV-2 (PASC). Identifying PASC and its subphenotypes is challenging because available data are \"negative-unlabeled\" as uninfected individuals must be PASC negative, but those with prior infection have unknown PASC status. Moreover, feature selection among many potentially informative characteristics can facilitate reaching a concise and easily interpretable PASC definition. Therefore, to characterize PASC and the spectrum of PASC subphenotypes while identifying a minimal set of features, we propose a Bernoulli mixture model with novel parameterization to accommodate negative-unlabeled data and Bayesian priors to induce sparsity. We present an efficient expectation-maximization algorithm for estimation, and a grid search procedure to select the number of clusters and level of sparsity. We evaluate the proposed method with a simulation study and an analysis of data on self-reported symptoms from the ongoing Researching COVID to Enhance Recovery-Adult Cohort study.","journal":"Biometrics","year":2025,"id":551996,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8885,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":933019,"name":"Harrison T. Reeder","orcid":"0000-0001-8813-9127","position":1,"is_corresponding":false},{"id":263591,"name":"Andrea S. Foulkes","orcid":"0000-0002-9520-0501","position":2,"is_corresponding":false},{"id":437652,"name":"Tingyi Cao","orcid":"0000-0002-4210-7127","position":0,"is_corresponding":true}],"reference_count":37,"raw_metadata":null,"created_at":"2026-07-19T02:54:29.318076Z","pmid":"40072491","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}