{"id":"https://openalex.org/W4391100358","doi":"https://doi.org/10.1145/3580252.3589415","title":"Demo: Addressing Inter-Intra Patient Variability via Personalized Meta-Federated Learning in IoT-Enabled Health Monitoring","display_name":"Demo: Addressing Inter-Intra Patient Variability via Personalized Meta-Federated Learning in IoT-Enabled Health Monitoring","publication_year":2023,"publication_date":"2023-06-21","ids":{"openalex":"https://openalex.org/W4391100358","doi":"https://doi.org/10.1145/3580252.3589415"},"language":"en","primary_location":{"id":"doi:10.1145/3580252.3589415","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580252.3589415","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580252.3589415","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th ACM/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3580252.3589415","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027997476","display_name":"Zhenge Jia","orcid":"https://orcid.org/0000-0002-0554-3608"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhenge Jia","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0002-0554-3608","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000141831","display_name":"Yiyu Shi","orcid":"https://orcid.org/0000-0002-6788-9823"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiyu Shi","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0002-6788-9823","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"175","last_page":"176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11932","display_name":"Wireless Body Area Networks","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11932","display_name":"Wireless Body Area Networks","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11446","display_name":"Mobile Health and mHealth Applications","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/3600","display_name":"General Health Professions"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.8539064526557922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7610894441604614},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.6703103184700012},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5726100206375122},{"id":"https://openalex.org/keywords/remote-patient-monitoring","display_name":"Remote patient monitoring","score":0.4874267876148224},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4285881519317627},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.38534101843833923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38010236620903015},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.2425146996974945},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.12302669882774353}],"concepts":[{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.8539064526557922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7610894441604614},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.6703103184700012},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5726100206375122},{"id":"https://openalex.org/C175079658","wikidata":"https://www.wikidata.org/wiki/Q7312165","display_name":"Remote patient monitoring","level":2,"score":0.4874267876148224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4285881519317627},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38534101843833923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38010236620903015},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2425146996974945},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.12302669882774353},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3580252.3589415","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580252.3589415","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580252.3589415","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th ACM/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3580252.3589415","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580252.3589415","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580252.3589415","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th ACM/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391100358.pdf","grobid_xml":"https://content.openalex.org/works/W4391100358.grobid-xml"},"referenced_works_count":2,"referenced_works":["https://openalex.org/W3190106860","https://openalex.org/W4220673118"],"related_works":["https://openalex.org/W4298221930","https://openalex.org/W4245926026","https://openalex.org/W4311097251","https://openalex.org/W2586548817","https://openalex.org/W2777914285","https://openalex.org/W2625093826","https://openalex.org/W3162204513","https://openalex.org/W2950174689","https://openalex.org/W4200598720","https://openalex.org/W2921026492"],"abstract_inverted_index":{"Federated":[0],"learning":[1,47],"(FL)":[2],"has":[3],"been":[4],"widely":[5],"adopted":[6],"in":[7,54],"IoT-enabled":[8],"health":[9,52,67],"monitoring":[10,53,68],"on":[11,70],"biosignals.":[12],"However,":[13],"the":[14,40,59,79],"global":[15],"model":[16],"may":[17],"not":[18],"adapt":[19],"well":[20],"to":[21,27],"each":[22],"target":[23],"patient's":[24],"data":[25],"due":[26],"complex":[28],"biosignals'":[29],"morphological":[30],"characteristics":[31],"caused":[32],"by":[33],"inter-":[34],"and":[35,61],"intra-patient":[36],"variability.":[37],"To":[38],"address":[39],"challenge,":[41],"we":[42,57],"propose":[43],"a":[44,71],"personalized":[45,89],"meta-federated":[46],"framework":[48],"(PMFed)":[49],"for":[50],"patient-specific":[51],"IoT.":[55],"Experimentally,":[56],"evaluate":[58],"effectiveness":[60],"generalization":[62],"of":[63],"PMFed":[64,80],"over":[65],"three":[66],"tasks":[69],"physical":[72],"IoT":[73],"platform.":[74],"Experimental":[75],"results":[76],"show":[77],"that":[78],"excels":[81],"at":[82],"empirical":[83],"performances":[84],"when":[85],"compared":[86],"with":[87],"SOTA":[88],"FL":[90],"algorithms.":[91]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
