{"id":"https://openalex.org/W7204276123","doi":"https://doi.org/10.14989/doctor.k26586","title":"AI\u8eab\u4f53\u6a5f\u80fd\u8a55\u4fa1\u30b7\u30b9\u30c6\u30e0\u69cb\u7bc9\u306b\u5411\u3051\u305f\u8a3a\u5bdf\u5ba4\u6a21\u5023\u52d5\u4f5c\u306e\u6163\u6027\u8a08\u6e2c\u88c5\u7f6e\u30c7\u30fc\u30bf\u89e3\u6790","display_name":"AI\u8eab\u4f53\u6a5f\u80fd\u8a55\u4fa1\u30b7\u30b9\u30c6\u30e0\u69cb\u7bc9\u306b\u5411\u3051\u305f\u8a3a\u5bdf\u5ba4\u6a21\u5023\u52d5\u4f5c\u306e\u6163\u6027\u8a08\u6e2c\u88c5\u7f6e\u30c7\u30fc\u30bf\u89e3\u6790","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7204276123","doi":"https://doi.org/10.14989/doctor.k26586"},"language":"en","primary_location":{"id":"pmh:oai:irdb.nii.ac.jp:01221:0007479459","doi":"https://doi.org/10.14989/doctor.k26586","is_oa":true,"landing_page_url":"http://hdl.handle.net/2433/302835","pdf_url":"https://repository.kulib.kyoto-u.ac.jp/bitstreams/bd924736-e968-48bc-a6aa-911f6e571df5/download","source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"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":null,"raw_type":"doctoral thesis"},"volume":null,"type":"dissertation","indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://repository.kulib.kyoto-u.ac.jp/bitstreams/bd924736-e968-48bc-a6aa-911f6e571df5/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019504867","display_name":"Nobuji Kouno","orcid":"https://orcid.org/0000-0003-2061-2111","observed_orcids":["https://orcid.org/0000-0003-2061-2111"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kouno, Nobuji","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5019504867"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"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/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.926800012588501,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.926800012588501,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.031599998474121094,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11011","display_name":"Frailty in Older Adults","score":0.029200000688433647,"subfield":{"id":"https://openalex.org/subfields/2717","display_name":"Geriatrics and Gerontology"},"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/physical-function-assessment","display_name":"physical function assessment","score":0.9589999914169312},{"id":"https://openalex.org/keywords/cancer-patients","display_name":"cancer patients","score":0.9610000252723694},{"id":"https://openalex.org/keywords/timed-up-and-go-test","display_name":"Timed Up and Go test","score":0.9020000100135803},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"inertial measurement unit","score":0.8769999742507935},{"id":"https://openalex.org/keywords/gait-analysis","display_name":"gait analysis","score":0.4790000021457672},{"id":"https://openalex.org/keywords/lasso","display_name":"LASSO","score":0.5709999799728394},{"id":"https://openalex.org/keywords/short-physical-performance-battery","display_name":"Short Physical Performance Battery","score":0.7789999842643738}],"concepts":[{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4357999861240387},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.43230000138282776},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.4004000127315521},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.37959998846054077},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.36329999566078186},{"id":"https://openalex.org/C2776048318","wikidata":"https://www.wikidata.org/wiki/Q7805516","display_name":"Timed Up and Go test","level":3,"score":0.3472999930381775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3246999979019165},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31310001015663147},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2865999937057495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28360000252723694},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28049999475479126},{"id":"https://openalex.org/C3020580240","wikidata":"https://www.wikidata.org/wiki/Q663272","display_name":"Expert opinion","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2800999879837036},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27720001339912415},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:irdb.nii.ac.jp:01221:0007479459","doi":"https://doi.org/10.14989/doctor.k26586","is_oa":true,"landing_page_url":"http://hdl.handle.net/2433/302835","pdf_url":"https://repository.kulib.kyoto-u.ac.jp/bitstreams/bd924736-e968-48bc-a6aa-911f6e571df5/download","source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"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":null,"raw_type":"doctoral thesis"},{"id":"pmh:oai:repository.kulib.kyoto-u.ac.jp:2433/302835","doi":"https://doi.org/10.14989/doctor.k26586","is_oa":true,"landing_page_url":"http://hdl.handle.net/2433/302835","pdf_url":null,"source":{"id":"https://openalex.org/S4306401454","display_name":"Kyoto University Research Information Repository (Kyoto University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I22299242","host_organization_name":"Kyoto University","host_organization_lineage":["https://openalex.org/I22299242"],"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":null,"raw_type":"doctoral thesis"}],"best_oa_location":{"id":"pmh:oai:irdb.nii.ac.jp:01221:0007479459","doi":"https://doi.org/10.14989/doctor.k26586","is_oa":true,"landing_page_url":"http://hdl.handle.net/2433/302835","pdf_url":"https://repository.kulib.kyoto-u.ac.jp/bitstreams/bd924736-e968-48bc-a6aa-911f6e571df5/download","source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"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":null,"raw_type":"doctoral thesis"},"sustainable_development_goals":[{"score":1.0,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G5725925787","display_name":null,"funder_award_id":"JPMJMS2295","funder_id":"https://openalex.org/F4320338247","funder_display_name":"Moonshot Research and Development Program"},{"id":"https://openalex.org/G6531407001","display_name":null,"funder_award_id":"JPMJMS2295\u201001","funder_id":"https://openalex.org/F4320338247","funder_display_name":"Moonshot Research and Development Program"},{"id":"https://openalex.org/G6789445021","display_name":null,"funder_award_id":"JPMJMS2295-01","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320335125","display_name":"RIKEN","ror":"https://ror.org/01sjwvz98"},{"id":"https://openalex.org/F4320338247","display_name":"Moonshot Research and Development Program","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204276123.pdf","grobid_xml":"https://content.openalex.org/works/W7204276123.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4405073768","https://openalex.org/W4404460516","https://openalex.org/W4399324867","https://openalex.org/W2070967636","https://openalex.org/W6946034014","https://openalex.org/W7161359945","https://openalex.org/W7165191164","https://openalex.org/W2089665410","https://openalex.org/W2769513067","https://openalex.org/W4412812418"],"abstract_inverted_index":{"Assessing":[0],"objective":[1],"physical":[2,32,58,193],"function":[3,59,194],"in":[4,45,107],"patients":[5,97],"with":[6,98,167,177],"cancer":[7,99],"is":[8],"crucial":[9],"for":[10,82,186,202],"evaluating":[11],"their":[12,43],"ability":[13],"to":[14,36,56,69,115,125],"tolerate":[15],"invasive":[16],"treatments.Current":[17],"assessment":[18,195],"methods,":[19],"such":[20],"as":[21,150],"the":[22,30,83,86,127,132,151,168,187,200],"timed":[23],"up":[24],"and":[25,29,40,67,120,162],"go":[26],"(TUG)":[27],"test":[28,129,180],"short":[31],"performance":[33],"battery,":[34],"tend":[35],"require":[37],"additional":[38,203],"resources":[39],"time,":[41],"limiting":[42],"practicality":[44],"routine":[46],"clinical":[47,65],"practice.To":[48],"address":[49],"these":[50],"challenges,":[51],"we":[52,88],"developed":[53,121],"a":[54,103,108,155,163,184],"system":[55,196],"assess":[57],"based":[60],"on":[61],"movements":[62,106],"observed":[63],"during":[64,79,172],"consultations":[66],"aimed":[68],"explore":[70],"relevant":[71],"features":[72],"from":[73,95],"inertial":[74,91],"measurement":[75,92],"unit":[76,93],"data":[77,94],"collected":[78,90],"those":[80],"movements.As":[81],"flow":[84],"of":[85,105,118,159,165,189],"research,":[87],"first":[89],"61":[96],"while":[100],"they":[101],"replicated":[102],"series":[104],"consultation":[109],"room.We":[110],"then":[111],"conducted":[112],"correlation":[113,164],"analyses":[114],"identify":[116],"keypoints":[117],"focus":[119],"machine":[122],"learning":[123],"models":[124],"predict":[126],"TUG":[128,170,179],"outcomes":[130],"using":[131,142,148],"extracted":[133],"features.Regarding":[134],"results,":[135],"pelvic":[136],"velocity":[137],"variability":[138],"(PVV)":[139],"was":[140],"identified":[141],"Lasso":[143],"regression.A":[144],"linear":[145],"regression":[146],"model":[147],"PVV":[149,175],"input":[152],"variable":[153],"achieved":[154],"mean":[156],"absolute":[157],"error":[158],"1.322":[160],"s":[161],"0.713":[166],"measured":[169],"results":[171],"five-fold":[173],"cross-validation.Higher":[174],"correlated":[176],"shorter":[178],"results.These":[181],"findings":[182],"provide":[183],"foundation":[185],"development":[188],"an":[190],"artificial":[191],"intelligence-based":[192],"that":[197],"operates":[198],"without":[199],"need":[201],"resources.":[204]},"counts_by_year":[],"updated_date":"2026-10-13T10:08:12.033832","created_date":"2026-08-27T00:00:00"}
