{"id":"https://openalex.org/W4390971353","doi":"https://doi.org/10.1109/bibm58861.2023.10385308","title":"Surgical Temporal Action-aware Network with Sequence Regularization for Phase Recognition","display_name":"Surgical Temporal Action-aware Network with Sequence Regularization for Phase Recognition","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390971353","doi":"https://doi.org/10.1109/bibm58861.2023.10385308"},"language":"en","primary_location":{"id":"doi:10.1109/bibm58861.2023.10385308","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-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":"https://openalex.org/A5002138702","display_name":"Zhen Chen","orcid":"https://orcid.org/0000-0001-5339-2499"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhen Chen","raw_affiliation_strings":["Hong Kong Institute of Science&#x0026;Innovation, Chinese Academy of Sciences,Centre for Artificial Intelligence and Robotics"],"affiliations":[{"raw_affiliation_string":"Hong Kong Institute of Science&#x0026;Innovation, Chinese Academy of Sciences,Centre for Artificial Intelligence and Robotics","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039776984","display_name":"Yuhao Zhai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210147433","display_name":"Beijing Friendship Hospital","ror":"https://ror.org/053qy4437","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210147433"]},{"id":"https://openalex.org/I183519381","display_name":"Capital Medical University","ror":"https://ror.org/013xs5b60","country_code":"CN","type":"education","lineage":["https://openalex.org/I183519381"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhao Zhai","raw_affiliation_strings":["Capital Medical University,Beijing Friendship Hospital","Beijing Friendship Hospital, Capital Medical University"],"affiliations":[{"raw_affiliation_string":"Capital Medical University,Beijing Friendship Hospital","institution_ids":["https://openalex.org/I4210147433"]},{"raw_affiliation_string":"Beijing Friendship Hospital, Capital Medical University","institution_ids":["https://openalex.org/I4210147433","https://openalex.org/I183519381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100433038","display_name":"Jun Zhang","orcid":"https://orcid.org/0000-0001-5411-1273"},"institutions":[{"id":"https://openalex.org/I4210147433","display_name":"Beijing Friendship Hospital","ror":"https://ror.org/053qy4437","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210147433"]},{"id":"https://openalex.org/I183519381","display_name":"Capital Medical University","ror":"https://ror.org/013xs5b60","country_code":"CN","type":"education","lineage":["https://openalex.org/I183519381"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhang","raw_affiliation_strings":["Capital Medical University,Beijing Friendship Hospital","Beijing Friendship Hospital, Capital Medical University"],"affiliations":[{"raw_affiliation_string":"Capital Medical University,Beijing Friendship Hospital","institution_ids":["https://openalex.org/I4210147433"]},{"raw_affiliation_string":"Beijing Friendship Hospital, Capital Medical University","institution_ids":["https://openalex.org/I4210147433","https://openalex.org/I183519381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058420913","display_name":"Jinqiao Wang","orcid":"https://orcid.org/0000-0002-9118-2780"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinqiao Wang","raw_affiliation_strings":["Hong Kong Institute of Science&#x0026;Innovation, Chinese Academy of Sciences,Centre for Artificial Intelligence and Robotics","Chinese Academy of Sciences, Institute of Automation","ObjectEye Inc","Wuhan AI Research"],"affiliations":[{"raw_affiliation_string":"Hong Kong Institute of Science&#x0026;Innovation, Chinese Academy of Sciences,Centre for Artificial Intelligence and Robotics","institution_ids":[]},{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Automation","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"ObjectEye Inc","institution_ids":[]},{"raw_affiliation_string":"Wuhan AI Research","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002138702"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6111,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.903633,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1836","last_page":"1841"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10916","display_name":"Surgical Simulation and Training","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10916","display_name":"Surgical Simulation and Training","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11984","display_name":"Anatomy and Medical Technology","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10888","display_name":"Augmented Reality Applications","score":0.9700999855995178,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7079091668128967},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5974205136299133},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5853779911994934},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5339682698249817},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4127300977706909},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.41022780537605286},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3943599462509155},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34595757722854614}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7079091668128967},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5974205136299133},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5853779911994934},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5339682698249817},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4127300977706909},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.41022780537605286},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3943599462509155},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34595757722854614},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm58861.2023.10385308","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2266464013","https://openalex.org/W2777273430","https://openalex.org/W2963853051","https://openalex.org/W2979536508","https://openalex.org/W2979797179","https://openalex.org/W2980110287","https://openalex.org/W2989744286","https://openalex.org/W2990152177","https://openalex.org/W3092562667","https://openalex.org/W3100964249","https://openalex.org/W3110266995","https://openalex.org/W3150630416","https://openalex.org/W3153757649","https://openalex.org/W3193657022","https://openalex.org/W3201659970","https://openalex.org/W3203204495","https://openalex.org/W3209030113","https://openalex.org/W3212407416","https://openalex.org/W4281253984","https://openalex.org/W4295312788","https://openalex.org/W4296195045","https://openalex.org/W4320713037","https://openalex.org/W4387225661","https://openalex.org/W4388231203","https://openalex.org/W6766978945","https://openalex.org/W6794114097"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"To":[0,98],"assist":[1],"surgeons":[2],"in":[3],"the":[4,42,86,148,156,163,168,198,214],"operating":[5],"theatre,":[6],"surgical":[7,15,22,62,93,117,130,145,190,202,226],"phase":[8,70,82,87,203,227],"recognition":[9],"is":[10],"critical":[11],"for":[12,69],"developing":[13],"computer-assisted":[14],"systems,":[16],"which":[17,64,135],"requires":[18],"comprehensive":[19],"understanding":[20],"of":[21,37,44,61,144,150,165,171,189,201,225],"videos.":[23,123],"Although":[24],"existing":[25],"studies":[26],"made":[27],"great":[28],"progress,":[29],"there":[30],"are":[31,50],"still":[32],"two":[33,101],"significant":[34],"limitations":[35],"worthy":[36],"improvement.":[38],"First,":[39],"due":[40],"to":[41,84,115,161,197],"compromise":[43],"resource":[45],"consumption,":[46],"framewise":[47],"visual":[48,137,187],"features":[49,138,188],"extracted":[51],"by":[52,167],"2D":[53,151],"networks":[54],"and":[55,58,89,141,183,213],"disregard":[56],"spatial":[57,140],"temporal":[59,131,142],"knowledge":[60,143],"actions,":[63],"hinders":[65],"subsequent":[66],"inter-frame":[67],"modeling":[68],"prediction.":[71],"Second,":[72],"these":[73,100],"works":[74],"simply":[75],"utilize":[76],"ordinary":[77],"classification":[78],"loss":[79],"with":[80,110,139,175,181,192],"one-hot":[81],"labels":[83],"optimize":[85],"predictions,":[88],"cannot":[90],"fully":[91],"explore":[92],"videos":[94],"under":[95],"inadequate":[96],"supervision.":[97],"overcome":[99],"limitations,":[102],"we":[103,125,154],"propose":[104,126],"a":[105,176,208],"Surgical":[106],"Temporal":[107],"Action-aware":[108],"Network":[109],"sequence":[111,158,169],"Regularization,":[112],"named":[113],"STAR-Net,":[114],"recognize":[116],"phases":[118],"more":[119],"accurately":[120],"from":[121],"input":[122],"Specifically,":[124],"an":[127,172],"efficient":[128],"multi-scale":[129],"action":[132],"(MS-STA)":[133],"module,":[134],"integrates":[136],"actions":[146,191],"at":[147],"cost":[149],"networks.":[152],"Moreover,":[153],"devise":[155],"dual-classifier":[157],"regularization":[159],"(DSR)":[160],"facilitate":[162],"training":[164],"STAR-Net":[166,180,221],"guidance":[170],"auxiliary":[173],"classifier":[174],"smaller":[177],"capacity.":[178],"Our":[179],"MS-STA":[182],"DSR":[184],"can":[185],"exploit":[186],"effective":[193],"regularization,":[194],"thereby":[195],"leading":[196],"superior":[199],"performance":[200],"recognition.":[204,228],"Extensive":[205],"experiments":[206],"on":[207],"large-scale":[209],"gastrectomy":[210],"surgery":[211],"dataset":[212],"public":[215],"Cholec80":[216],"benchmark":[217],"prove":[218],"that":[219],"our":[220],"significantly":[222],"outperforms":[223],"state-of-the-arts":[224]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
