{"id":"https://openalex.org/W4401635490","doi":"https://doi.org/10.3233/jcm-247563","title":"Performance of long short-term memory networks in predicting athlete injury risk","display_name":"Performance of long short-term memory networks in predicting athlete injury risk","publication_year":2024,"publication_date":"2024-08-14","ids":{"openalex":"https://openalex.org/W4401635490","doi":"https://doi.org/10.3233/jcm-247563"},"language":"en","primary_location":{"id":"doi:10.3233/jcm-247563","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jcm-247563","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","raw_type":"journal-article"},"type":"article","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":null,"display_name":"Hong Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116144","display_name":"Chongqing University of Education","ror":"https://ror.org/02d06s578","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210116144"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Tao","raw_affiliation_strings":["School of Physical Education, Chongqing Preschool Education College, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physical Education, Chongqing Preschool Education College, Chongqing, China","institution_ids":["https://openalex.org/I4210116144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110526847","display_name":"Yue Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116144","display_name":"Chongqing University of Education","ror":"https://ror.org/02d06s578","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210116144"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Deng","raw_affiliation_strings":["School of Physical Education, Chongqing Preschool Education College, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physical Education, Chongqing Preschool Education College, Chongqing, China","institution_ids":["https://openalex.org/I4210116144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111293054","display_name":"Yunqiu Xiang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116144","display_name":"Chongqing University of Education","ror":"https://ror.org/02d06s578","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210116144"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunqiu Xiang","raw_affiliation_strings":["School of Physical Education, Chongqing Preschool Education College, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physical Education, Chongqing Preschool Education College, Chongqing, China","institution_ids":["https://openalex.org/I4210116144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115595933","display_name":"Long Liu","orcid":"https://orcid.org/0009-0003-6108-2097"},"institutions":[{"id":"https://openalex.org/I4210116144","display_name":"Chongqing University of Education","ror":"https://ror.org/02d06s578","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210116144"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Long Liu","raw_affiliation_strings":["School of Physical Education, Chongqing Preschool Education College, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physical Education, Chongqing Preschool Education College, Chongqing, China","institution_ids":["https://openalex.org/I4210116144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5115595933"],"corresponding_institution_ids":["https://openalex.org/I4210116144"],"apc_list":null,"apc_paid":null,"fwci":0.2414,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54187961,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"24","issue":"4-5","first_page":"3155","last_page":"3171"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9704999923706055,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9704999923706055,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8057529926300049},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.6749191880226135},{"id":"https://openalex.org/keywords/scope","display_name":"Scope (computer science)","score":0.5971534848213196},{"id":"https://openalex.org/keywords/athletes","display_name":"Athletes","score":0.5769095420837402},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5149794220924377},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46910935640335083},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4391426742076874},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.37945809960365295},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3264496624469757}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8057529926300049},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.6749191880226135},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.5971534848213196},{"id":"https://openalex.org/C2781054738","wikidata":"https://www.wikidata.org/wiki/Q4813730","display_name":"Athletes","level":2,"score":0.5769095420837402},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5149794220924377},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46910935640335083},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4391426742076874},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.37945809960365295},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3264496624469757},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jcm-247563","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jcm-247563","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2605764466","https://openalex.org/W2608799779","https://openalex.org/W2624385633","https://openalex.org/W2768151880","https://openalex.org/W2781388396","https://openalex.org/W2784562102","https://openalex.org/W2786687024","https://openalex.org/W2790897772","https://openalex.org/W2798244167","https://openalex.org/W2800819102","https://openalex.org/W2807280045","https://openalex.org/W2811471078","https://openalex.org/W2896827527","https://openalex.org/W2900542332","https://openalex.org/W2905730354","https://openalex.org/W2912371425","https://openalex.org/W2915656893","https://openalex.org/W2950416458","https://openalex.org/W2964006806","https://openalex.org/W3019396605","https://openalex.org/W3135400423","https://openalex.org/W3151387141","https://openalex.org/W3180895085","https://openalex.org/W3194074702","https://openalex.org/W3206795426","https://openalex.org/W4205134630","https://openalex.org/W4205495647"],"related_works":["https://openalex.org/W2912153778","https://openalex.org/W4387163678","https://openalex.org/W4288108708","https://openalex.org/W2973430807","https://openalex.org/W4385280324","https://openalex.org/W2890685186","https://openalex.org/W2984436043","https://openalex.org/W4390245176","https://openalex.org/W2912831041","https://openalex.org/W3173606726"],"abstract_inverted_index":{"Conventional":[0],"approaches":[1],"to":[2,20,44,49,100,113,163,176],"forecasting":[3],"the":[4,27,35,55,61,71,77,83,88,102,115,118,130,148,161,166,181],"risk":[5,62,134,173],"of":[6,29,59,63,70,87,117,139,143,150,170,180],"athlete":[7,132,152,171],"injuries":[8,64,185],"are":[9],"constrained":[10],"by":[11],"their":[12],"narrow":[13],"scope":[14],"in":[15,137,186],"feature":[16],"extraction,":[17],"often":[18],"failing":[19],"adequately":[21],"account":[22],"for":[23,147],"temporal":[24,46,84,151,182],"dependencies":[25],"and":[26,57,76,106,168],"effects":[28],"long-term":[30],"memory.":[31],"This":[32,51,158],"paper":[33],"enhances":[34],"Long":[36],"Short-Term":[37],"Memory":[38],"(LSTM)":[39],"network,":[40],"specifically":[41],"tailoring":[42],"it":[43],"harness":[45],"data":[47,79,85,93,153],"pertaining":[48],"athletes.":[50,66],"advancement":[52],"significantly":[53],"boosts":[54],"accuracy":[56,167],"effectiveness":[58,169],"predicting":[60],"among":[65],"The":[67,122,141],"network":[68,125],"structure":[69],"LSTM":[72,89,104,120,124,145],"model":[73,126,136],"was":[74,80,111,127],"improved,":[75],"collected":[78],"converted":[81],"into":[82],"form":[86],"input.":[90],"Finally,":[91],"historical":[92],"labeled":[94],"with":[95,129],"injury":[96,133,172],"labels":[97],"were":[98],"used":[99,112],"train":[101],"improved":[103,119,123],"model,":[105],"gradient":[107],"descent":[108],"iterative":[109],"optimization":[110],"adjust":[114],"parameters":[116],"model.":[121],"compared":[128],"traditional":[131],"prediction":[135],"terms":[138],"performance.":[140],"incorporation":[142],"enhanced":[144],"networks":[146],"analysis":[149],"holds":[154],"significant":[155],"research":[156],"significance.":[157],"approach":[159],"has":[160],"potential":[162],"substantially":[164],"enhance":[165],"prediction,":[174],"contributing":[175],"a":[177],"deeper":[178],"understanding":[179],"dynamics":[183],"influencing":[184],"sports.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}