{"doi":"10.1161/strokeaha.125.050447","title":"Distributed Precision Stroke Care: Artificial Intelligence-Driven Stroke Management Using Multimodal Sensor Data","abstract":"<jats:p>Delays in stroke diagnosis contribute to long-term disability. Many patients still face barriers to effective risk factor management, timely detection, and access to poststroke rehabilitation. The emergence of artificial intelligence–enabled, consumer-facing health technologies offers a transformative opportunity to address these gaps across the stroke care continuum. This review examines the evolving role of artificial intelligence-powered devices, including smartwatches, smartphones, wearable sensors, and ambient home-based technologies, in enabling precision stroke care. For stroke prevention, these tools facilitate scalable monitoring of cardiometabolic and stroke-specific risk factors. For early detection, artificial intelligence algorithms applied to multimodal sensor data can identify subtle neurological impairments and support real-time triage. In recovery, artificial intelligence-enhanced remote monitoring and virtual supervision offer scalable models for delivering personalized rehabilitation outside of specialized centers. Although most of these innovations remain in early development, they signal a paradigm shift toward accessible, individualized, and data-driven stroke prevention and management.</jats:p>","journal":"Stroke","year":2026,"id":649329,"datarank":0.38474240361923057,"base_score":2.5649493574615367,"endowment":2.5649493574615367,"self_citation_contribution":0.38474240361923057,"citation_network_contribution":0.0,"self_endowment_contribution":0.38474240361923057,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":12,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":249914,"name":"Lee H. Schwamm","orcid":"0000-0003-0592-9145","position":1,"is_corresponding":false},{"id":74880,"name":"Rohan Khera","orcid":"0000-0001-9467-6199","position":2,"is_corresponding":false},{"id":1326923,"name":"Aline F Pedroso","orcid":"0000-0002-1876-8304","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Distributed Precision Stroke Care: Artificial Intelligence-Driven Stroke Management Using Multimodal Sensor Data","abstract":"<jats:p>Delays in stroke diagnosis contribute to long-term disability. Many patients still face barriers to effective risk factor management, timely detection, and access to poststroke rehabilitation. The emergence of artificial intelligence–enabled, consumer-facing health technologies offers a transformative opportunity to address these gaps across the stroke care continuum. This review examines the evolving role of artificial intelligence-powered devices, including smartwatches, smartphones, wearable sensors, and ambient home-based technologies, in enabling precision stroke care. For stroke prevention, these tools facilitate scalable monitoring of cardiometabolic and stroke-specific risk factors. For early detection, artificial intelligence algorithms applied to multimodal sensor data can identify subtle neurological impairments and support real-time triage. In recovery, artificial intelligence-enhanced remote monitoring and virtual supervision offer scalable models for delivering personalized rehabilitation outside of specialized centers. Although most of these innovations remain in early development, they signal a paradigm shift toward accessible, individualized, and data-driven stroke prevention and management.</jats:p>","is_dataset_classified":null,"base_score":2.3978952727983707,"endowment":2.3978952727983707,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"41122835","pmcid":"PMC12616450","openalex_id":"https://openalex.org/W4415407551","authors":[],"funders":[{"funder_name":"NIA NIH HHS","grant_id":"R01 AG089981","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"K23 HL153775","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"R01 HL167858","title":null}],"total_grants":3,"fwci":7.4832,"citation_percentile":0.97880209,"influential_citations":0,"citation_trend":[{"year":2026,"count":10}],"oa_status":"green","license":null,"oa_locations":[{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12616450/","host_type":"repository"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12616450/","host_type":"repository"},{"url":"https://www.ahajournals.org/doi/full/10.1161/STROKEAHA.125.050447","host_type":"publisher"},{"url":"https://doi.org/10.1161/strokeaha.125.050447","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/41122835","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12616450","host_type":"repository"}],"fields_of_study":["Acute Ischemic Stroke Management","Stroke Rehabilitation and Recovery","Cerebrovascular and Carotid Artery Diseases","Medicine","Engineering","Computer Science","Humans","Stroke","Artificial Intelligence","Precision Medicine","Stroke Rehabilitation","Wearable Electronic Devices","Telemedicine"],"mesh_terms":["Stroke Rehabilitation","Wearable Electronic Devices","Artificial Intelligence","Humans","Telemedicine","Stroke","Precision Medicine"],"keywords":["Stroke (engine)","Wearable computer","Rehabilitation","Scalability","Wearable technology","Telemedicine","mHealth","Artificial neural network","Artificial intelligence","Atrial fibrillation","Smartphone","Community Healthcare","Precision Medicine","Digital Health"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"doi"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-10T03:32:57.491685Z","pmid":null,"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":[]}