{"id":"https://openalex.org/W4402052968","doi":"https://doi.org/10.3390/e26090740","title":"Adaptive Top-K Algorithm for Medical Conversational Diagnostic Model","display_name":"Adaptive Top-K Algorithm for Medical Conversational Diagnostic Model","publication_year":2024,"publication_date":"2024-08-30","ids":{"openalex":"https://openalex.org/W4402052968","doi":"https://doi.org/10.3390/e26090740","pmid":"https://pubmed.ncbi.nlm.nih.gov/39330074"},"language":"en","primary_location":{"id":"doi:10.3390/e26090740","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/e26090740","pdf_url":"https://www.mdpi.com/1099-4300/26/9/740/pdf?version=1725000718","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/26/9/740/pdf?version=1725000718","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048444584","display_name":"Yiqing Yang","orcid":"https://orcid.org/0009-0003-2888-7846"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqing Yang","raw_affiliation_strings":["Department of Computer Science, Harbin Engineering University, Harbin 150001, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Harbin Engineering University, Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074415234","display_name":"Guoyin Zhang","orcid":"https://orcid.org/0000-0003-4833-1741"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoyin Zhang","raw_affiliation_strings":["Department of Computer Science, Harbin Engineering University, Harbin 150001, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Harbin Engineering University, Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027083552","display_name":"Yanxia Wu","orcid":"https://orcid.org/0000-0001-8384-9234"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanxia Wu","raw_affiliation_strings":["Department of Computer Science, Harbin Engineering University, Harbin 150001, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Harbin Engineering University, Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101179025","display_name":"Zhixiang Zhao","orcid":"https://orcid.org/0009-0008-6555-1897"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixiang Zhao","raw_affiliation_strings":["Department of Computer Science, Harbin Engineering University, Harbin 150001, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Harbin Engineering University, Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102773413","display_name":"Yan Fu","orcid":"https://orcid.org/0000-0001-9943-7656"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Fu","raw_affiliation_strings":["Department of Computer Science, Harbin Engineering University, Harbin 150001, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Harbin Engineering University, Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5027083552"],"corresponding_institution_ids":["https://openalex.org/I151727225"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12176654,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"9","first_page":"740","last_page":"740"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9829000234603882,"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/T10028","display_name":"Topic Modeling","score":0.9829000234603882,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9713000059127808,"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/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.9550999999046326,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.582843542098999},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5507093071937561},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3449054956436157}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.582843542098999},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5507093071937561},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3449054956436157}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e26090740","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/e26090740","pdf_url":"https://www.mdpi.com/1099-4300/26/9/740/pdf?version=1725000718","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:39330074","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39330074","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11431395","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11431395","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11431395/pdf/entropy-26-00740.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:2e6f61328c034999a68312eb98983900","is_oa":true,"landing_page_url":"https://doaj.org/article/2e6f61328c034999a68312eb98983900","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 26, Iss 9, p 740 (2024)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/26/9/740/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e26090740","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Entropy","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e26090740","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/e26090740","pdf_url":"https://www.mdpi.com/1099-4300/26/9/740/pdf?version=1725000718","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402052968.pdf","grobid_xml":"https://content.openalex.org/works/W4402052968.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W2173564293","https://openalex.org/W2260756217","https://openalex.org/W2788477667","https://openalex.org/W2886305736","https://openalex.org/W2903928064","https://openalex.org/W3011594683","https://openalex.org/W3192100427","https://openalex.org/W3212838894","https://openalex.org/W4225882738","https://openalex.org/W4226103537","https://openalex.org/W4283075950","https://openalex.org/W4306313008","https://openalex.org/W4379280015","https://openalex.org/W4386457054","https://openalex.org/W4390578128","https://openalex.org/W4391144542","https://openalex.org/W4399943982"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"With":[0],"advancements":[1],"in":[2,18,25,65,92],"computing":[3],"technology":[4],"and":[5,101,118,145,160,188,191],"the":[6,46,54,104,110,116,131,138,141,154,162,169,173,184,193,202],"rapid":[7],"progress":[8],"of":[9,48,56,106,120,140,150,165,186],"data":[10],"science,":[11],"machine":[12],"learning":[13],"has":[14],"been":[15,35],"widely":[16],"applied":[17],"various":[19],"fields,":[20],"showing":[21],"great":[22],"potential,":[23],"especially":[24],"digital":[26],"healthcare.":[27],"In":[28],"recent":[29],"years,":[30],"conversational":[31],"diagnostic":[32,75,87,122,155,174],"systems":[33,44,79,91],"have":[34],"used":[36],"to":[37,73,80,85,97,201],"predict":[38],"diseases":[39,72,144,189],"through":[40,176],"symptom":[41],"checking.":[42],"Early":[43],"predicted":[45],"likelihood":[47],"a":[49,177],"single":[50],"disease":[51],"by":[52,147,197],"minimizing":[53],"number":[55,139,185],"questions":[57,84],"asked.":[58],"However,":[59],"doctors":[60],"typically":[61],"perform":[62],"differential":[63,107,204],"diagnoses":[64],"real":[66],"medical":[67,94],"practice,":[68],"considering":[69],"multiple":[70],"possible":[71],"address":[74],"uncertainty.":[76],"This":[77,134],"requires":[78],"ask":[81],"more":[82],"critical":[83],"improve":[86,115],"accuracy.":[88],"Nevertheless,":[89],"such":[90],"acute":[93],"situations":[95],"need":[96],"process":[98],"information":[99],"quickly":[100],"accurately,":[102],"but":[103],"complexity":[105],"diagnosis":[108,205],"increases":[109],"system's":[111,194],"computational":[112],"cost.":[113],"To":[114],"efficiency":[117],"accuracy":[119,158],"telemedicine":[121],"systems,":[123],"this":[124],"study":[125],"developed":[126],"an":[127],"optimized":[128],"algorithm":[129,135,171],"for":[130],"Top-K":[132,170],"algorithm.":[133],"dynamically":[136],"adjusts":[137],"most":[142],"likely":[143],"symptoms":[146,187],"real-time":[148],"monitoring":[149],"case":[151],"progress,":[152],"optimizing":[153],"process,":[156],"enhancing":[157],"(99.81%),":[159],"increasing":[161],"exclusion":[163],"rate":[164],"severe":[166],"pathologies.":[167],"Additionally,":[168],"optimizes":[172],"model":[175],"policy":[178],"network":[179],"loss":[180],"function,":[181],"effectively":[182],"reducing":[183],"processed":[190],"improving":[192],"response":[195],"speed":[196],"1.3-1.9":[198],"times":[199],"compared":[200],"state-of-the-art":[203],"systems.":[206]},"counts_by_year":[],"updated_date":"2026-03-13T14:20:09.374765","created_date":"2025-10-10T00:00:00"}