{"id":"https://openalex.org/W4407837700","doi":"https://doi.org/10.3233/978-1-61499-830-3-604","title":"A Deep Learning-Based Method for Similar Patient Question Retrieval in Chinese","display_name":"A Deep Learning-Based Method for Similar Patient Question Retrieval in Chinese","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W4407837700","doi":"https://doi.org/10.3233/978-1-61499-830-3-604"},"language":"en","primary_location":{"id":"doi:10.3233/978-1-61499-830-3-604","is_oa":false,"landing_page_url":"https://doi.org/10.3233/978-1-61499-830-3-604","pdf_url":null,"source":{"id":"https://openalex.org/S4210179765","display_name":"Studies in health technology and informatics","issn_l":"0926-9630","issn":["0926-9630","1879-8365"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies in Health Technology and Informatics","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001777175","display_name":"Tao Yu","orcid":"https://orcid.org/0000-0003-4167-4127"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang Guo Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112115522","display_name":"Yuan Ni","orcid":"https://orcid.org/0000-0002-9672-3531"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ni Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Xie Guo Tong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie Guo Tong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100373560","display_name":"Fan Li","orcid":"https://orcid.org/0000-0002-2348-4488"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan Xin Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5046466790","display_name":"Shi Yong Ling","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi Yan Ling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44987562,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9362999796867371,"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":0.9362999796867371,"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/computer-science","display_name":"Computer science","score":0.7123717069625854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6323969960212708},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5888254046440125},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.47299036383628845},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.43006014823913574},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3401743173599243}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7123717069625854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6323969960212708},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5888254046440125},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.47299036383628845},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.43006014823913574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3401743173599243}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/978-1-61499-830-3-604","is_oa":false,"landing_page_url":"https://doi.org/10.3233/978-1-61499-830-3-604","pdf_url":null,"source":{"id":"https://openalex.org/S4210179765","display_name":"Studies in health technology and informatics","issn_l":"0926-9630","issn":["0926-9630","1879-8365"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies in Health Technology and Informatics","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W4387369504","https://openalex.org/W3046775127"],"abstract_inverted_index":{"The":[0,112,146],"online":[1],"patient":[2,90],"question":[3,60,70,91],"and":[4,29,158],"answering":[5],"(Q&amp;amp;A)":[6],"system,":[7],"either":[8],"as":[9,118],"a":[10,13,55,67,80,122,127],"website":[11],"or":[12],"mobile":[14],"application,":[15],"attracts":[16],"an":[17],"increasing":[18],"number":[19],"of":[20,41,50],"users":[21],"in":[22,92],"China.":[23],"Patients":[24],"will":[25],"post":[26],"their":[27],"questions":[28,42],"the":[30,35,52,57,72,88,105,109,119,133,141],"registered":[31],"doctors":[32,46],"then":[33,116],"provide":[34],"corresponding":[36],"answers.":[37],"A":[38],"large":[39],"amount":[40],"with":[43],"answers":[44],"from":[45,54,71],"are":[47],"accumulated.":[48],"Instead":[49],"awaiting":[51],"response":[53],"doctor,":[56],"newly":[58],"posted":[59],"could":[61],"be":[62],"quickly":[63],"answered":[64],"by":[65],"finding":[66],"semantically":[68],"equivalent":[69],"Q&amp;amp;A":[73],"achive.":[74],"In":[75],"this":[76],"study,":[77],"we":[78],"investigated":[79],"novel":[81],"deep":[82,99,129],"learning":[83,96,124],"based":[84],"method":[85,153],"to":[86,107,121,139],"retrieve":[87],"similar":[89],"Chinese.":[93],"An":[94],"unsupervised":[95],"algorithm":[97,125],"using":[98,126],"neural":[100,130,135],"network":[101],"is":[102],"performed":[103],"on":[104],"corpus":[106],"generate":[108],"word":[110,113],"embedding.":[111],"embedding":[114],"was":[115],"used":[117],"input":[120],"supervised":[123,134],"designed":[128],"network,":[131],"i.e.":[132],"attention":[136],"model":[137],"(SNA),":[138],"predict":[140],"similarity":[142],"between":[143],"two":[144],"questions.":[145],"experimental":[147],"results":[148],"showed":[149],"that":[150],"our":[151],"SNA":[152],"achieved":[154],"P@1":[155],"=":[156,160],"77%":[157],"P@5":[159],"84%,":[161],"which":[162],"outperformed":[163],"all":[164],"other":[165],"compared":[166],"methods.":[167]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
