{"id":"https://openalex.org/W4385730011","doi":"https://doi.org/10.1145/3594806.3596577","title":"An integrated framework for classifying mammograms according to BIRADS scale and breast tissue density.","display_name":"An integrated framework for classifying mammograms according to BIRADS scale and breast tissue density.","publication_year":2023,"publication_date":"2023-07-05","ids":{"openalex":"https://openalex.org/W4385730011","doi":"https://doi.org/10.1145/3594806.3596577"},"language":"en","primary_location":{"id":"doi:10.1145/3594806.3596577","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3594806.3596577","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3594806.3596577","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3594806.3596577","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044031662","display_name":"Ioannis N. Tzortzis","orcid":"https://orcid.org/0000-0003-0942-6166"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Ioannis Tzortzis","raw_affiliation_strings":["Department of Rural and Surveying Engineering and Geoinformatics Engineering, National Technical University of Athens, Greece"],"raw_orcid":"https://orcid.org/0000-0003-0942-6166","affiliations":[{"raw_affiliation_string":"Department of Rural and Surveying Engineering and Geoinformatics Engineering, National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044082782","display_name":"Stavros Sykiotis","orcid":"https://orcid.org/0000-0001-7013-0626"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Stavros Sykiotis","raw_affiliation_strings":["Department of Rural and Surveying Engineering and Geoinformatics Engineering, National Technical University of Athens, Greece"],"raw_orcid":"https://orcid.org/0000-0001-7013-0626","affiliations":[{"raw_affiliation_string":"Department of Rural and Surveying Engineering and Geoinformatics Engineering, National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057865801","display_name":"Ioannis Rallis","orcid":"https://orcid.org/0000-0003-4491-5854"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Ioannis Rallis","raw_affiliation_strings":["Department of Rural and Surveying Engineering and Geoinformatics Engineering, National Technical University of Athens, Greece"],"raw_orcid":"https://orcid.org/0000-0003-4491-5854","affiliations":[{"raw_affiliation_string":"Department of Rural and Surveying Engineering and Geoinformatics Engineering, National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033117805","display_name":"Nikolaos Doulamis","orcid":null},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nikolaos Doulamis","raw_affiliation_strings":["Department of Rural and Surveying Engineering and Geoinformatics Engineering, National Technical University of Athens, Greece"],"raw_orcid":"https://orcid.org/0000-0002-4064-8990","affiliations":[{"raw_affiliation_string":"Department of Rural and Surveying Engineering and Geoinformatics Engineering, National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5044031662"],"corresponding_institution_ids":["https://openalex.org/I174458059"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09370197,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"728","last_page":"731"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998000264167786,"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":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11361","display_name":"Digital Radiography and Breast Imaging","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9908999800682068,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6953778266906738},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6264708042144775},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6155535578727722},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5359312891960144},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4943110942840576},{"id":"https://openalex.org/keywords/f1-score","display_name":"F1 score","score":0.483864426612854},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.47799983620643616},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4428776800632477},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4384726285934448},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4279758632183075},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.427101731300354}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6953778266906738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6264708042144775},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6155535578727722},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5359312891960144},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4943110942840576},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.483864426612854},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47799983620643616},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4428776800632477},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4384726285934448},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4279758632183075},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.427101731300354},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3594806.3596577","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3594806.3596577","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3594806.3596577","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3594806.3596577","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3594806.3596577","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3594806.3596577","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G1525016749","display_name":null,"funder_award_id":"952179","funder_id":"https://openalex.org/F4320334322","funder_display_name":"HORIZON EUROPE Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320334322","display_name":"HORIZON EUROPE Framework Programme","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385730011.pdf","grobid_xml":"https://content.openalex.org/works/W4385730011.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W304373761","https://openalex.org/W2109285035","https://openalex.org/W2754958205","https://openalex.org/W2928842276","https://openalex.org/W2946053491","https://openalex.org/W3023402959","https://openalex.org/W3082480095","https://openalex.org/W3083403771","https://openalex.org/W3110148606","https://openalex.org/W3165997322","https://openalex.org/W4210426211","https://openalex.org/W4220750587","https://openalex.org/W4294189863","https://openalex.org/W4300690596","https://openalex.org/W4303628880"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2055243143","https://openalex.org/W2770593030","https://openalex.org/W4321487865","https://openalex.org/W3154990682","https://openalex.org/W4313906399","https://openalex.org/W2560201613","https://openalex.org/W2171975302","https://openalex.org/W2022352247","https://openalex.org/W4391266461"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"present":[4],"an":[5],"integrated":[6],"framework":[7],"for":[8,66,76],"classifying":[9],"digital":[10],"or":[11,19],"digitized":[12],"mammograms":[13],"according":[14],"to":[15,46,81],"either":[16],"BIRADS":[17,108],"scale":[18],"breast":[20],"density":[21],"score.":[22],"We":[23,59],"propose":[24],"unified":[25],"data":[26],"preparation":[27],"procedure,":[28],"a":[29,35,41,55,63],"common":[30],"training":[31,67],"process":[32],"that":[33],"includes":[34],"Convolutional":[36],"Neural":[37],"Network":[38],"approach":[39],"and":[40,53,68,91,98,103],"simple":[42],"inference":[43],"tool":[44],"aiming":[45],"ensure":[47],"the":[48,72,77],"robustness":[49],"of":[50],"out":[51],"model":[52],"provide":[54],"more":[56],"generalized":[57],"solution.":[58],"utilize":[60],"not":[61],"only":[62],"private":[64],"dataset":[65,74],"validation,":[69],"but":[70],"also":[71],"open":[73],"INBreast":[75],"testing":[78],"procedure.":[79],"According":[80],"our":[82,84],"results,":[83],"solution":[85],"achieves;":[86],"a)":[87],"accuracy":[88,100],"score":[89,93,101,105],"87%":[90],"F1":[92,104],"82%":[94],"on":[95,107],"Density":[96],"classification,":[97],"b)":[99],"85%":[102],"80%":[106],"classification.":[109]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
