{"id":"https://openalex.org/W2315312789","doi":"https://doi.org/10.1117/12.2216550","title":"An adaptive online learning framework for practical breast cancer diagnosis","display_name":"An adaptive online learning framework for practical breast cancer diagnosis","publication_year":2016,"publication_date":"2016-03-24","ids":{"openalex":"https://openalex.org/W2315312789","doi":"https://doi.org/10.1117/12.2216550","mag":"2315312789"},"language":"en","primary_location":{"id":"doi:10.1117/12.2216550","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2216550","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5101737502","display_name":"Tianshu Chu","orcid":"https://orcid.org/0000-0002-9404-3348"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tianshu Chu","raw_affiliation_strings":["Stanford Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stanford Univ. (United States)","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101422661","display_name":"Jie Wang","orcid":"https://orcid.org/0000-0003-1857-5569"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jie Wang","raw_affiliation_strings":["Stanford Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stanford Univ. (United States)","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100380049","display_name":"Jiayu Chen","orcid":"https://orcid.org/0000-0002-7708-5247"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiayu Chen","raw_affiliation_strings":["GE Healthcare (United States)"],"affiliations":[{"raw_affiliation_string":"GE Healthcare (United States)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101737502"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":0.857,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.82923038,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"9785","issue":null,"first_page":"978524","last_page":"978524"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9668999910354614,"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/T10862","display_name":"AI in cancer detection","score":0.9668999910354614,"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":0.6615712642669678},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.6494379043579102},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.338242769241333},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32214999198913574},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.18598085641860962},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.07919144630432129}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6615712642669678},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.6494379043579102},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.338242769241333},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32214999198913574},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.18598085641860962},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.07919144630432129}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2216550","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2216550","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1831403251","https://openalex.org/W1969557815","https://openalex.org/W1976070030","https://openalex.org/W1983181208","https://openalex.org/W1987915768","https://openalex.org/W2002262117","https://openalex.org/W2013840898","https://openalex.org/W2019605179","https://openalex.org/W2052234900","https://openalex.org/W2066393173","https://openalex.org/W2076337359","https://openalex.org/W2110243528","https://openalex.org/W2110485192","https://openalex.org/W2111061352","https://openalex.org/W2116709052","https://openalex.org/W2151161180","https://openalex.org/W2162307063","https://openalex.org/W2162376722","https://openalex.org/W2165664908","https://openalex.org/W2169982856","https://openalex.org/W2189916683","https://openalex.org/W2333661806","https://openalex.org/W3021359142","https://openalex.org/W4211221179","https://openalex.org/W4233696721","https://openalex.org/W4256499626","https://openalex.org/W6638565613","https://openalex.org/W6703105651"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W2382290278"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"an":[3],"adaptive":[4],"online":[5,100],"learning":[6,80,89],"(OL)":[7],"framework":[8,33,56,76,120,189],"for":[9,83,92],"supporting":[10],"clinical":[11,73,95],"breast":[12],"cancer":[13],"(BC)":[14],"diagnosis.":[15],"Unlike":[16],"traditional":[17],"data":[18,46,210],"mining,":[19],"which":[20],"trains":[21],"a":[22,26,53,110],"particular":[23],"model":[24,125,146,177],"from":[25,193,208],"fixed":[27],"set":[28],"of":[29,94,181],"medical":[30],"data,":[31],"our":[32,55,119,200],"offers":[34],"robust":[35],"OL":[36,188],"models":[37,82,91,142,202,221],"that":[38,199,217],"can":[39,57,121,138,168],"be":[40],"updated":[41],"adaptively":[42],"according":[43],"to":[44,60],"new":[45],"sequences":[47],"and":[48,87,102,108,148,173,195,197,211],"newly":[49],"discovered":[50],"features.":[51,213],"As":[52],"result,":[54],"naturally":[58],"learn":[59],"perform":[61],"BC":[62,84,205],"diagnosis":[63,116,130],"using":[64],"experts\u2019":[65],"opinions":[66],"on":[67,128,190],"sequential":[68,209],"patient":[69],"cases":[70],"with":[71,105],"cumulative":[72,183],"measurements.":[74,96],"The":[75],"integrates":[77],"both":[78],"supervised":[79],"(SL)":[81],"risk":[85,206],"assessment":[86,207],"reinforcement":[88],"(RL)":[90],"decision-making":[93],"In":[97],"other":[98],"words,":[99],"SL":[101,201],"RL":[103,220],"interact":[104],"one":[106],"another,":[107],"under":[109],"doctor\u2019s":[111],"supervision,":[112],"push":[113],"the":[114,133,151,155,162,170,175,182,187,218],"patient\u2019s":[115],"further.":[117],"Furthermore,":[118],"quickly":[122],"update":[123],"relevant":[124],"parameters":[126,153,172],"based":[127],"current":[129],"information":[131],"during":[132,154],"training":[134],"process.":[135,159],"Additionally,":[136],"it":[137,167],"build":[139],"flexible":[140],"fitted":[141],"by":[143],"integrating":[144],"different":[145],"structures":[147],"plugging":[149],"in":[150],"corresponding":[152,171],"prediction":[156],"(or":[157],"decision-making)":[158],"Even":[160],"when":[161],"feature":[163],"space":[164],"is":[165],"extended,":[166],"initialize":[169],"extend":[174],"existing":[176],"structure":[178],"without":[179],"loss":[180],"knowledge.":[184],"We":[185,214],"evaluate":[186],"real":[191],"datasets":[192],"BCSC":[194],"WBC,":[196],"demonstrate":[198],"achieve":[203],"accurate":[204],"incremental":[212],"also":[215],"verify":[216],"well-trained":[219],"provide":[222],"promising":[223],"measurement":[224],"suggestions.":[225]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
