{"id":"https://openalex.org/W4393407217","doi":"https://doi.org/10.1109/aiccsa59173.2023.10479339","title":"A Thermographic Time Series Approach for Evaluating the Breast Cancer Treatment","display_name":"A Thermographic Time Series Approach for Evaluating the Breast Cancer Treatment","publication_year":2023,"publication_date":"2023-12-04","ids":{"openalex":"https://openalex.org/W4393407217","doi":"https://doi.org/10.1109/aiccsa59173.2023.10479339"},"language":"en","primary_location":{"id":"doi:10.1109/aiccsa59173.2023.10479339","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/aiccsa59173.2023.10479339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA)","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/A5023021035","display_name":"Adriel S. Araujo","orcid":"https://orcid.org/0000-0003-0637-8007"},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]},{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["BR","ES"],"is_corresponding":false,"raw_author_name":"Adriel S. Araujo","raw_affiliation_strings":["Fluminense Federal University,Institute of Computing,Niter&#x00F3;i,Brazil","Technical School of Computer Science, Rey Juan Carlos University, Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fluminense Federal University,Institute of Computing,Niter&#x00F3;i,Brazil","institution_ids":["https://openalex.org/I161127581"]},{"raw_affiliation_string":"Technical School of Computer Science, Rey Juan Carlos University, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034421186","display_name":"Milena H. S. Issa","orcid":null},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Milena H. S. Issa","raw_affiliation_strings":["Fluminense Federal University,Faculty of Medicine,Niter&#x00F3;i,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fluminense Federal University,Faculty of Medicine,Niter&#x00F3;i,Brazil","institution_ids":["https://openalex.org/I161127581"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jo\u00e3o V. S. Chagas","orcid":null},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jo\u00e3o V. S. Chagas","raw_affiliation_strings":["Fluminense Federal University,Institute of Computing,Niter&#x00F3;i,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fluminense Federal University,Institute of Computing,Niter&#x00F3;i,Brazil","institution_ids":["https://openalex.org/I161127581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060281689","display_name":"\u00c1ngel S\u00e1nchez","orcid":"https://orcid.org/0000-0001-9069-6985"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"\u00c1ngel S\u00e1nchez","raw_affiliation_strings":["Rey Juan Carlos University,Technical School of Computer Science,Madrid,Spain","Technical School of Computer Science, Rey Juan Carlos University, Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rey Juan Carlos University,Technical School of Computer Science,Madrid,Spain","institution_ids":["https://openalex.org/I182083151"]},{"raw_affiliation_string":"Technical School of Computer Science, Rey Juan Carlos University, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017693414","display_name":"D\u00e9bora C. Muchaluat-Saade","orcid":"https://orcid.org/0000-0002-1233-9736"},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"D\u00e9bora C. Muchaluat-Saade","raw_affiliation_strings":["Fluminense Federal University,Institute of Computing,Niter&#x00F3;i,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fluminense Federal University,Institute of Computing,Niter&#x00F3;i,Brazil","institution_ids":["https://openalex.org/I161127581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5094304651","display_name":"Aura Concia","orcid":null},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Aura Concia","raw_affiliation_strings":["Fluminense Federal University,Institute of Computing,Niter&#x00F3;i,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fluminense Federal University,Institute of Computing,Niter&#x00F3;i,Brazil","institution_ids":["https://openalex.org/I161127581"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"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":0.4136868,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12994","display_name":"Infrared Thermography in Medicine","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T12994","display_name":"Infrared Thermography in Medicine","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11856","display_name":"Thermography and Photoacoustic Techniques","score":0.9595999717712402,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T13539","display_name":"thermodynamics and calorimetric analyses","score":0.9434999823570251,"subfield":{"id":"https://openalex.org/subfields/1606","display_name":"Physical and Theoretical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.7030800580978394},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.6447222232818604},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4843255281448364},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4310232698917389},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.35604074597358704},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22027447819709778},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.189077228307724},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.13084334135055542},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.07168775796890259}],"concepts":[{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.7030800580978394},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.6447222232818604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4843255281448364},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4310232698917389},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.35604074597358704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22027447819709778},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.189077228307724},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.13084334135055542},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.07168775796890259},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aiccsa59173.2023.10479339","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/aiccsa59173.2023.10479339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1486879195","https://openalex.org/W1495426342","https://openalex.org/W1562848178","https://openalex.org/W2060161052","https://openalex.org/W2299451239","https://openalex.org/W2325015832","https://openalex.org/W2410937062","https://openalex.org/W2596199005","https://openalex.org/W2597875610","https://openalex.org/W2604024202","https://openalex.org/W2729967392","https://openalex.org/W2791080843","https://openalex.org/W2793174164","https://openalex.org/W2800428700","https://openalex.org/W2897983644","https://openalex.org/W2939550773","https://openalex.org/W2987100639","https://openalex.org/W2997797021","https://openalex.org/W3011776598","https://openalex.org/W3035761923","https://openalex.org/W3046595073","https://openalex.org/W3122705032","https://openalex.org/W3142213751","https://openalex.org/W3174499504","https://openalex.org/W3181932191","https://openalex.org/W3186821473","https://openalex.org/W3190820488","https://openalex.org/W4253306460","https://openalex.org/W6680970901","https://openalex.org/W6788686789"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"One":[0],"of":[1,6,21,67,76,153,164],"the":[2,18,22,74,96,102,107,114,134,145,154,159,165,169,175],"most":[3],"prevalent":[4],"types":[5],"cancer":[7,77],"worldwide":[8],"is":[9],"breast":[10,61],"cancer,":[11],"a":[12,26,64],"condition":[13],"that":[14,29,141],"tends":[15],"to":[16,46,72,82,112,132],"change":[17],"thermal":[19,103,130],"pattern":[20],"breasts.":[23],"Thermographic":[24],"images,":[25],"functional":[27],"examination":[28,50,71],"considers":[30],"temperature":[31,44],"variation,":[32],"emerge":[33],"as":[34],"an":[35],"alternative":[36],"for":[37,57],"this":[38,70,88,142],"disease":[39],"since":[40],"they":[41],"consider":[42],"body":[43],"variation":[45],"investigate":[47,69],"anomalies.":[48],"This":[49,84],"has":[51],"been":[52],"widely":[53],"investigated":[54],"in":[55,87,149],"studies":[56,68],"screening":[58],"or":[59],"diagnosing":[60],"cancer.":[62],"However,":[63],"limited":[65],"number":[66],"track":[73],"progress":[75],"and":[78,105,126,162,171],"assess":[79],"tumor":[80,136],"response":[81],"treatment.":[83,94],"study":[85],"works":[86],"context,":[89],"exploring":[90],"thermography":[91],"during":[92],"neoadjuvant":[93],"In":[95],"proposed":[97],"methodology,":[98],"we":[99,118],"first":[100],"preprocess":[101],"data":[104],"use":[106],"k-means":[108],"unsupervised":[109],"learning":[110],"algorithm":[111],"identify":[113],"hottest":[115],"regions.":[116],"Subsequently,":[117],"build":[119],"time":[120],"series":[121],"based":[122],"on":[123,174],"statistical":[124,160,170],"measures":[125,128,161,173],"homogeneity":[127,172],"among":[129],"captures":[131],"evaluate":[133],"patients\u2019":[135],"evolution.":[137],"The":[138],"results":[139],"show":[140],"approach":[143],"indicates":[144],"treatment":[146],"evolution":[147],"correctly":[148],"at":[150],"least":[151],"79%":[152],"cases":[155,166],"when":[156,167],"observing":[157],"only":[158],"95%":[163],"combining":[168],"patient":[176],"evaluation":[177],"process.":[178]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
