{"doi":"10.1109/tbme.2025.3613293","title":"Heart Rate Variability via Poincaré Mapping as an Early Biomarker Post-Cardiac Arrest","abstract":"BACKGROUND: Predicting neurological outcomes following cardiac arrest remains challenging. This study introduces a two-stage approach that combines a novel feature selection optimization with machine learning classification, utilizing heart rate variability (HRV) features for early and reliable prognostication. METHODS: A rodent model resuscitated after a 7-min arrest was used. Features based on classic HRV and advanced Poincaré vector mapping were extracted. An Ant Colony Optimization method with Dynamic Pheromone Decay and Knowledge Distillation (ACO-DPKD) was employed for efficient feature optimization due to its ability to adaptively prioritize complex feature interactions. Selected features were classified using a support vector machine. RESULTS: ACO-DPKD identified key HRV features, enabling accurate prediction of neurological outcomes within 1 hour of resuscitation, achieving 90% accuracy. Integration of advanced Poincaré metrics with traditional HRV features improved prediction accuracy by approximately 20%, underscoring their clinical relevance for early neurological assessment. SIGNIFICANCE: Optimized classification within the critical first hour after cardiac arrest lays the foundation for timely neuroprotective interventions, with advanced Poincaré vector features playing a major role in driving early prognostic accuracy.","journal":"IEEE Transactions on Biomedical Engineering","year":2025,"id":536724,"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":0.9602,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"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":729939,"name":"Yu Guo","orcid":"0000-0002-6802-0708","position":1,"is_corresponding":false},{"id":449447,"name":"Payam Gharibani","orcid":"0000-0002-4546-0890","position":2,"is_corresponding":false},{"id":495290,"name":"Anastasios Bezerianos","orcid":"0000-0002-8199-6000","position":3,"is_corresponding":false},{"id":510530,"name":"Romergryko G. Geocadin","orcid":"0000-0002-6618-5656","position":4,"is_corresponding":false},{"id":495292,"name":"Nitish V. Thakor","orcid":"0000-0002-9981-9395","position":5,"is_corresponding":false},{"id":1422052,"name":"Prachi Agarwal","orcid":"0000-0003-2037-837X","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-19T02:52:09.056872Z","pmid":"40986595","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":[]}