{"id":"https://openalex.org/W4294647531","doi":"https://doi.org/10.1186/s13040-022-00303-z","title":"Learning and visualizing chronic latent representations using electronic health records","display_name":"Learning and visualizing chronic latent representations using electronic health records","publication_year":2022,"publication_date":"2022-09-05","ids":{"openalex":"https://openalex.org/W4294647531","doi":"https://doi.org/10.1186/s13040-022-00303-z","pmid":"https://pubmed.ncbi.nlm.nih.gov/36064616"},"language":"en","primary_location":{"id":"doi:10.1186/s13040-022-00303-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13040-022-00303-z","pdf_url":"https://biodatamining.biomedcentral.com/counter/pdf/10.1186/s13040-022-00303-z","source":{"id":"https://openalex.org/S84409260","display_name":"BioData Mining","issn_l":"1756-0381","issn":["1756-0381"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData Mining","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://biodatamining.biomedcentral.com/counter/pdf/10.1186/s13040-022-00303-z","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018305051","display_name":"David Chushig-Muzo","orcid":"https://orcid.org/0000-0001-5585-2305"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"David Chushig-Muzo","raw_affiliation_strings":["Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0001-5585-2305","affiliations":[{"raw_affiliation_string":"Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084198564","display_name":"Cristina Soguero-Ru\u00edz","orcid":"https://orcid.org/0000-0001-5817-989X"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Cristina Soguero-Ruiz","raw_affiliation_strings":["Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088291579","display_name":"Pablo de Miguel-Bohoyo","orcid":"https://orcid.org/0000-0001-5241-596X"},"institutions":[{"id":"https://openalex.org/I4210149026","display_name":"Hospital Universitario de Fuenlabrada","ror":"https://ror.org/04scbtr44","country_code":"ES","type":"healthcare","lineage":["https://openalex.org/I4210139293","https://openalex.org/I4210149026"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Pablo de Miguel Bohoyo","raw_affiliation_strings":["University Hospital of Fuenlabrada, Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University Hospital of Fuenlabrada, Madrid, Spain","institution_ids":["https://openalex.org/I4210149026"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091890497","display_name":"Inmaculada Mora-Jim\u00e9nez","orcid":"https://orcid.org/0000-0003-0735-367X"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Inmaculada Mora-Jim\u00e9nez","raw_affiliation_strings":["Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain. inmaculada.mora@urjc.es","Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0003-0735-367X","affiliations":[{"raw_affiliation_string":"Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain. inmaculada.mora@urjc.es","institution_ids":["https://openalex.org/I182083151"]},{"raw_affiliation_string":"Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5018305051"],"corresponding_institution_ids":["https://openalex.org/I182083151"],"apc_list":{"value":1690,"currency":"GBP","value_usd":2072},"apc_paid":{"value":1690,"currency":"GBP","value_usd":2072},"fwci":0.971,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.79806101,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"15","issue":"1","first_page":"18","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9406999945640564,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9406999945640564,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.006599999964237213,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"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/T12246","display_name":"Chronic Disease Management Strategies","score":0.006000000052154064,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/autoencoder","display_name":"Autoencoder","score":0.6458086371421814},{"id":"https://openalex.org/keywords/health-records","display_name":"Health records","score":0.5863065719604492},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.5561352372169495},{"id":"https://openalex.org/keywords/gestational-diabetes","display_name":"Gestational diabetes","score":0.5326499342918396},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5005364418029785},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.4787430167198181},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.45061883330345154},{"id":"https://openalex.org/keywords/chronic-disease","display_name":"Chronic disease","score":0.44905781745910645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4442068636417389},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.4196421504020691},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.41506415605545044},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4086993932723999},{"id":"https://openalex.org/keywords/intensive-care-medicine","display_name":"Intensive care medicine","score":0.33292922377586365},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3314947783946991},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2844162583351135},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.23810303211212158},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.12421673536300659}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6458086371421814},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.5863065719604492},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.5561352372169495},{"id":"https://openalex.org/C2779434492","wikidata":"https://www.wikidata.org/wiki/Q126691","display_name":"Gestational diabetes","level":4,"score":0.5326499342918396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5005364418029785},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4787430167198181},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.45061883330345154},{"id":"https://openalex.org/C2987552334","wikidata":"https://www.wikidata.org/wiki/Q383126","display_name":"Chronic disease","level":2,"score":0.44905781745910645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4442068636417389},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.4196421504020691},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.41506415605545044},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4086993932723999},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.33292922377586365},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3314947783946991},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2844162583351135},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.23810303211212158},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.12421673536300659},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C46973012","wikidata":"https://www.wikidata.org/wiki/Q28627","display_name":"Gestation","level":3,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C2779234561","wikidata":"https://www.wikidata.org/wiki/Q11995","display_name":"Pregnancy","level":2,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1186/s13040-022-00303-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13040-022-00303-z","pdf_url":"https://biodatamining.biomedcentral.com/counter/pdf/10.1186/s13040-022-00303-z","source":{"id":"https://openalex.org/S84409260","display_name":"BioData Mining","issn_l":"1756-0381","issn":["1756-0381"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData Mining","raw_type":"journal-article"},{"id":"pmid:36064616","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36064616","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData mining","raw_type":null},{"id":"pmh:oai:doaj.org/article:c7effac20a4b40f68e5d3ea442f12930","is_oa":true,"landing_page_url":"https://doaj.org/article/c7effac20a4b40f68e5d3ea442f12930","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BioData Mining, Vol 15, Iss 1, Pp 1-27 (2022)","raw_type":"article"},{"id":"pmh:oai:eciencia.urjc.es:10115/28495","is_oa":true,"landing_page_url":"https://hdl.handle.net/10115/28495","pdf_url":null,"source":{"id":"https://openalex.org/S4377196484","display_name":"BURJC Digital (King Juan Carlos University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I182083151","host_organization_name":"Universidad Rey Juan Carlos","host_organization_lineage":["https://openalex.org/I182083151"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:pubmedcentral.nih.gov:9446539","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9446539","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BioData Min","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s13040-022-00303-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13040-022-00303-z","pdf_url":"https://biodatamining.biomedcentral.com/counter/pdf/10.1186/s13040-022-00303-z","source":{"id":"https://openalex.org/S84409260","display_name":"BioData Mining","issn_l":"1756-0381","issn":["1756-0381"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData Mining","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5600582317","display_name":null,"funder_award_id":"PID2019-107768RA-I00","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G6799522020","display_name":null,"funder_award_id":"DTS17/00158","funder_id":"https://openalex.org/F4320334923","funder_display_name":"Instituto de Salud Carlos III"},{"id":"https://openalex.org/G6982243727","display_name":null,"funder_award_id":"TEC2016-75361-R","funder_id":"https://openalex.org/F4320326262","funder_display_name":"Ministerio de Asuntos Econ\u00f3micos y Transformaci\u00f3n Digital, Gobierno de Espa\u00f1a"},{"id":"https://openalex.org/G7036153705","display_name":null,"funder_award_id":"PID2019-106623RB-C41","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"}],"funders":[{"id":"https://openalex.org/F4320313831","display_name":"Comunidad de Madrid","ror":null},{"id":"https://openalex.org/F4320326262","display_name":"Ministerio de Asuntos Econ\u00f3micos y Transformaci\u00f3n Digital, Gobierno de Espa\u00f1a","ror":"https://ror.org/03sv46s19"},{"id":"https://openalex.org/F4320334923","display_name":"Instituto de Salud Carlos III","ror":"https://ror.org/00ca2c886"},{"id":"https://openalex.org/F4320335598","display_name":"Agencia Estatal de Investigaci\u00f3n","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4294647531.pdf","grobid_xml":"https://content.openalex.org/works/W4294647531.grobid-xml"},"referenced_works_count":69,"referenced_works":["https://openalex.org/W82250859","https://openalex.org/W1506806321","https://openalex.org/W1808652302","https://openalex.org/W1842840699","https://openalex.org/W1922474554","https://openalex.org/W1956239603","https://openalex.org/W1967017916","https://openalex.org/W1973825638","https://openalex.org/W1978804804","https://openalex.org/W1985059878","https://openalex.org/W1988918323","https://openalex.org/W2004203864","https://openalex.org/W2011430131","https://openalex.org/W2017978677","https://openalex.org/W2020473483","https://openalex.org/W2025768430","https://openalex.org/W2033250946","https://openalex.org/W2033454243","https://openalex.org/W2042954874","https://openalex.org/W2062573090","https://openalex.org/W2062686485","https://openalex.org/W2074226299","https://openalex.org/W2074307717","https://openalex.org/W2097368998","https://openalex.org/W2100495367","https://openalex.org/W2102354326","https://openalex.org/W2104374197","https://openalex.org/W2118978333","https://openalex.org/W2120435692","https://openalex.org/W2121382432","https://openalex.org/W2127218421","https://openalex.org/W2135781475","https://openalex.org/W2137686028","https://openalex.org/W2143413851","https://openalex.org/W2147663252","https://openalex.org/W2158703410","https://openalex.org/W2160805609","https://openalex.org/W2254039850","https://openalex.org/W2289846183","https://openalex.org/W2404901863","https://openalex.org/W2524000875","https://openalex.org/W2557301950","https://openalex.org/W2591832038","https://openalex.org/W2752973482","https://openalex.org/W2760217853","https://openalex.org/W2790350670","https://openalex.org/W2796511697","https://openalex.org/W2808897169","https://openalex.org/W2857237370","https://openalex.org/W2883924858","https://openalex.org/W2887036440","https://openalex.org/W2950562763","https://openalex.org/W2951915646","https://openalex.org/W2963174546","https://openalex.org/W2975605169","https://openalex.org/W3004465995","https://openalex.org/W3008420520","https://openalex.org/W3010692414","https://openalex.org/W3011193648","https://openalex.org/W3045495939","https://openalex.org/W3111073730","https://openalex.org/W3141188857","https://openalex.org/W3146143520","https://openalex.org/W3187897714","https://openalex.org/W3193534298","https://openalex.org/W3213375231","https://openalex.org/W3213952842","https://openalex.org/W4211157329","https://openalex.org/W4249344264"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W2145836866","https://openalex.org/W2803255133"],"abstract_inverted_index":{"BACKGROUND:":[0],"Nowadays,":[1],"patients":[2,134,193,209,227,265,295],"with":[3,67,99,112,135,194,210,228,275,296],"chronic":[4,137,214,276,298],"diseases":[5,17],"such":[6],"as":[7,313],"diabetes":[8,200],"and":[9,25,31,60,201,235,238,247,272,323],"hypertension":[10,246],"have":[11],"reached":[12],"alarming":[13],"numbers":[14],"worldwide.":[15],"These":[16],"increase":[18],"the":[19,64,73,76,96,108,121,131,148,159,176,186,211,259,268,282,292,301,307],"risk":[20],"of":[21,39,75,110,133,155,179,189,225,242,255,263,284,294],"developing":[22],"acute":[23],"complications":[24],"involve":[26],"a":[27,80,113,125,240,253,314],"substantial":[28],"economic":[29],"burden":[30],"demand":[32],"for":[33,48,257,316],"health":[34,150,260,303,321],"resources.":[35],"The":[36,203],"widespread":[37],"adoption":[38],"Electronic":[40],"Health":[41],"Records":[42],"(EHRs)":[43],"is":[44,154],"opening":[45],"great":[46,187],"opportunities":[47],"supporting":[49,291],"decision-making.":[50],"Nevertheless,":[51],"data":[52,89,123,170],"extracted":[53,171],"from":[54,172],"EHRs":[55,173],"are":[56],"complex":[57],"(heterogeneous,":[58],"high-dimensional":[59,88],"usually":[61],"noisy),":[62],"hampering":[63],"knowledge":[65,129],"extraction":[66],"conventional":[68],"approaches.":[69],"METHODS:":[70],"We":[71,102,250],"propose":[72],"use":[74],"Denoising":[77],"Autoencoder":[78],"(DAE),":[79],"Machine":[81],"Learning":[82],"(ML)":[83],"technique":[84],"allowing":[85],"to":[86,119,146,175,191,198,207,287,319],"transform":[87],"into":[90],"latent":[91],"representations":[92],"(LRs),":[93],"thus":[94],"addressing":[95],"main":[97,213],"challenges":[98],"clinical":[100,160,165,195,218,289,328],"data.":[101],"explore":[103],"in":[104,124,158,181,230],"this":[105,140],"work":[106],"how":[107],"combination":[109],"LRs":[111],"visualization":[114],"method":[115],"can":[116,142],"be":[117,143,311],"used":[118,145,312],"map":[120],"patient":[122],"two-dimensional":[126,308],"space,":[127],"gaining":[128],"about":[130],"distribution":[132],"different":[136,217],"conditions.":[138,299],"Furthermore,":[139,300],"representation":[141],"also":[144,239,251],"characterize":[147,320],"patient's":[149,302],"status":[151,261,304],"evolution,":[152],"which":[153],"paramount":[156],"importance":[157],"setting.":[161],"RESULTS:":[162],"To":[163],"obtain":[164],"LRs,":[166],"we":[167,221],"considered":[168],"real-world":[169],"linked":[174,197],"University":[177],"Hospital":[178],"Fuenlabrada":[180],"Spain.":[182],"Experimental":[183],"results":[184,280],"showed":[185],"potential":[188],"DAEs":[190],"identify":[192,324],"patterns":[196],"hypertension,":[199],"multimorbidity.":[202],"procedure":[204],"allowed":[205],"us":[206],"find":[208],"same":[212],"disease":[215],"but":[216],"characteristics.":[219],"Thus,":[220],"identified":[222],"two":[223],"kinds":[224],"diabetic":[226],"differences":[229],"their":[231,325],"drug":[232],"therapy":[233],"(insulin":[234],"non-insulin":[236],"dependant),":[237],"group":[241],"women":[243],"affected":[244],"by":[245],"gestational":[248],"diabetes.":[249],"present":[252],"proof":[254],"concept":[256],"mapping":[258],"evolution":[262],"synthetic":[264],"when":[266],"considering":[267],"most":[269],"significant":[270],"diagnoses":[271],"drugs":[273],"associated":[274],"patients.":[277],"CONCLUSION:":[278],"Our":[279],"highlighted":[281],"value":[283],"ML":[285],"techniques":[286],"extract":[288],"knowledge,":[290],"identification":[293],"certain":[297],"progression":[305],"on":[306],"space":[309],"might":[310],"tool":[315],"clinicians":[317],"aiming":[318],"conditions":[322],"more":[326],"relevant":[327],"codes.":[329]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
