{"id":"https://openalex.org/W3097912645","doi":"https://doi.org/10.23919/fruct50888.2021.9347605","title":"An Extensive Survey of Machine Learning Based Approaches on Automated Pathology Detection in Chest X-Rays","display_name":"An Extensive Survey of Machine Learning Based Approaches on Automated Pathology Detection in Chest X-Rays","publication_year":2021,"publication_date":"2021-01-27","ids":{"openalex":"https://openalex.org/W3097912645","doi":"https://doi.org/10.23919/fruct50888.2021.9347605","mag":"3097912645"},"language":"en","primary_location":{"id":"doi:10.23919/fruct50888.2021.9347605","is_oa":false,"landing_page_url":"https://doi.org/10.23919/fruct50888.2021.9347605","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 28th Conference of Open Innovations Association (FRUCT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doaj.org/article/7bc814d8c6f04076af7a8b97a403d694","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080210758","display_name":"Ravidu Suien Rammuni Silva","orcid":"https://orcid.org/0000-0003-2525-1300"},"institutions":[{"id":"https://openalex.org/I94951947","display_name":"University of Westminster","ror":"https://ror.org/04ycpbx82","country_code":"GB","type":"education","lineage":["https://openalex.org/I94951947"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ravidu Suien Rammuni Silva","raw_affiliation_strings":["University of Westminster,London,UK","University of Westminster, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Westminster,London,UK","institution_ids":["https://openalex.org/I94951947"]},{"raw_affiliation_string":"University of Westminster, London, UK","institution_ids":["https://openalex.org/I94951947"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016117343","display_name":"Pumudu Fernando","orcid":"https://orcid.org/0000-0003-2049-5349"},"institutions":[{"id":"https://openalex.org/I6358929","display_name":"Informatics Institute of Technology","ror":"https://ror.org/02366kp40","country_code":"LK","type":"education","lineage":["https://openalex.org/I6358929"]}],"countries":["LK"],"is_corresponding":false,"raw_author_name":"Pumudu Fernando","raw_affiliation_strings":["Informatics Institute of Technology,Colombo,Sri Lanka","Informatics Institute of Technology, Colombo, Sri Lanka"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Informatics Institute of Technology,Colombo,Sri Lanka","institution_ids":["https://openalex.org/I6358929"]},{"raw_affiliation_string":"Informatics Institute of Technology, Colombo, Sri Lanka","institution_ids":["https://openalex.org/I6358929"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2868,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.54910046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"365","last_page":"373"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998000264167786,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998000264167786,"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/T10862","display_name":"AI in cancer detection","score":0.9966999888420105,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9958999752998352,"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":0.7131308317184448},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6902235746383667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6155368089675903},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5959746241569519},{"id":"https://openalex.org/keywords/radiography","display_name":"Radiography","score":0.5765878558158875},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5546494722366333},{"id":"https://openalex.org/keywords/thoracic-diseases","display_name":"Thoracic diseases","score":0.4811645448207855},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.46870750188827515},{"id":"https://openalex.org/keywords/medical-physics","display_name":"Medical physics","score":0.3418281674385071},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3002001643180847},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.20869490504264832}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7131308317184448},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6902235746383667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6155368089675903},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5959746241569519},{"id":"https://openalex.org/C36454342","wikidata":"https://www.wikidata.org/wiki/Q245341","display_name":"Radiography","level":2,"score":0.5765878558158875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5546494722366333},{"id":"https://openalex.org/C2909566329","wikidata":"https://www.wikidata.org/wiki/Q994554","display_name":"Thoracic diseases","level":2,"score":0.4811645448207855},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.46870750188827515},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3418281674385071},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3002001643180847},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.20869490504264832}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.23919/fruct50888.2021.9347605","is_oa":false,"landing_page_url":"https://doi.org/10.23919/fruct50888.2021.9347605","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 28th Conference of Open Innovations Association (FRUCT)","raw_type":"proceedings-article"},{"id":"pmh:oai:doaj.org/article:7bc814d8c6f04076af7a8b97a403d694","is_oa":true,"landing_page_url":"https://doaj.org/article/7bc814d8c6f04076af7a8b97a403d694","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 28, Iss 1, Pp 365-373 (2021)","raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:doaj.org/article:7bc814d8c6f04076af7a8b97a403d694","is_oa":true,"landing_page_url":"https://doaj.org/article/7bc814d8c6f04076af7a8b97a403d694","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 28, Iss 1, Pp 365-373 (2021)","raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1519798095","https://openalex.org/W1570613334","https://openalex.org/W1578632676","https://openalex.org/W1600365733","https://openalex.org/W1904878066","https://openalex.org/W1964625659","https://openalex.org/W1986086122","https://openalex.org/W2013706164","https://openalex.org/W2038952578","https://openalex.org/W2063878321","https://openalex.org/W2064362294","https://openalex.org/W2064675550","https://openalex.org/W2068816753","https://openalex.org/W2081189277","https://openalex.org/W2084220915","https://openalex.org/W2101891738","https://openalex.org/W2115597079","https://openalex.org/W2122402213","https://openalex.org/W2132731342","https://openalex.org/W2139865360","https://openalex.org/W2142514727","https://openalex.org/W2145260909","https://openalex.org/W2147094580","https://openalex.org/W2147800946","https://openalex.org/W2151251813","https://openalex.org/W2152772232","https://openalex.org/W2156235098","https://openalex.org/W2157981225","https://openalex.org/W2237401284","https://openalex.org/W2534171296","https://openalex.org/W2557738935","https://openalex.org/W2584017349","https://openalex.org/W2778310824","https://openalex.org/W2786052267","https://openalex.org/W2794103425","https://openalex.org/W2799108307","https://openalex.org/W2884149198","https://openalex.org/W2901794879","https://openalex.org/W2907071956","https://openalex.org/W2948093896","https://openalex.org/W2949698495","https://openalex.org/W2963420686","https://openalex.org/W2963446712","https://openalex.org/W2963466845","https://openalex.org/W2963942157","https://openalex.org/W3044844141","https://openalex.org/W3101156210","https://openalex.org/W3103194435","https://openalex.org/W3122459568","https://openalex.org/W4295608163","https://openalex.org/W4297439931","https://openalex.org/W4300485340","https://openalex.org/W4394659038"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W3024479225","https://openalex.org/W4323287533"],"abstract_inverted_index":{"Radiography":[0],"is":[1,19],"one":[2],"of":[3,26,30,145],"the":[4,13,33,46,106,130,135,143,151,154],"most":[5],"common":[6],"and":[7,23,36,43,81,93,103,141,167],"eminent":[8],"medical":[9],"imaging":[10],"technologies":[11],"in":[12,38,59,86,113,162,172],"world":[14],"to":[15],"date.":[16],"Chest":[17,87,97,124,180],"radiography":[18,61],"a":[20,114,158],"very":[21],"powerful":[22],"successful":[24],"way":[25],"diagnosing":[27],"thoracic":[28],"diseases":[29],"humans.":[31],"With":[32],"latest":[34],"advancements":[35],"development":[37],"computer":[39,41],"hardware,":[40],"vision":[42],"especially":[44],"with":[45,100,157,160,170],"publicly":[47,94],"available":[48,95],"large-scale":[49],"datasets,":[50],"machine":[51,76,137],"learning":[52,77,138],"based":[53,175],"approaches":[54],"on":[55,74,83,179],"automated":[56,176],"pathology":[57,84,177],"detection":[58,85,178],"chest":[60],"have":[62],"become":[63],"increasingly":[64],"popular":[65,92,118],"among":[66],"researchers.":[67],"Our":[68],"study":[69],"conducts":[70],"an":[71],"extensive":[72],"survey":[73],"existing":[75],"approaches,":[78],"its":[79,101],"datasets":[80,99],"techniques":[82,122],"X-Rays.":[88,181],"The":[89],"paper":[90,131,155],"presents":[91],"labelled":[96],"X-Rays":[98,125],"specifications":[102],"discusses":[104,133],"about":[105,134],"labellers,":[107],"labelling":[108],"methodologies":[109],"used":[110,140],"by":[111],"them":[112,171],"comprehensive":[115],"discussion.":[116],"Then,":[117],"effective":[119],"Image":[120],"Processing":[121],"for":[123,150],"images":[126],"are":[127],"presented.":[128],"Then":[129],"further":[132],"current":[136,163],"architectures":[139],"portraits":[142],"effectiveness":[144],"Deep":[146],"Convolutional":[147],"Neural":[148],"Networks":[149],"purpose.":[152],"Finally,":[153],"concludes":[156],"discussion":[159],"gaps":[161],"literature,":[164],"unexplored":[165],"areas":[166],"possible":[168],"future":[169],"Machine":[173],"Learning":[174]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
