{"id":"https://openalex.org/W3034709671","doi":null,"title":"Deep Transfer Learning with Apache Spark to Detect COVID-19 in chest X-ray Images","display_name":"Deep Transfer Learning with Apache Spark to Detect COVID-19 in chest X-ray Images","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3034709671","mag":"3034709671"},"language":"en","primary_location":{"id":"mag:3034709671","doi":null,"is_oa":false,"landing_page_url":"https://pesquisa.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/resource/en/covidwho-599056","pdf_url":null,"source":{"id":"https://openalex.org/S151779546","display_name":"Romanian Journal of Information Science and Technology","issn_l":"1453-8245","issn":["1453-8245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","norway-1","poland-20","russia-white-list-3"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Romanian Journal of Information Science and Technology","raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5000319390","display_name":"Houssam Benbrahim","orcid":"https://orcid.org/0000-0001-9409-6928","observed_orcids":["https://orcid.org/0000-0001-9409-6928"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Houssam Benbrahim","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9409-6928","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065452451","display_name":"Hana\u00e2 Hachimi","orcid":"https://orcid.org/0000-0001-6884-083X","observed_orcids":["https://orcid.org/0000-0001-6884-083X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hana\u00e2 Hachimi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5079804245","display_name":"Aouatif Amine","orcid":"https://orcid.org/0000-0002-6806-3513","observed_orcids":["https://orcid.org/0000-0002-6806-3513"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aouatif Amine","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1189,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.93825307,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":"23","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"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":1.0,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0,"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/sars-cov-2-detection","display_name":"COVID-19 detection","score":0.9980000257492065},{"id":"https://openalex.org/keywords/chest-x-ray-images","display_name":"chest X-ray images","score":0.9879999756813049},{"id":"https://openalex.org/keywords/deep-transfer-learning","display_name":"deep transfer learning","score":0.8579999804496765},{"id":"https://openalex.org/keywords/apache-spark","display_name":"Apache Spark","score":0.921999990940094},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8690000176429749},{"id":"https://openalex.org/keywords/inception-v3","display_name":"InceptionV3","score":0.9990000128746033},{"id":"https://openalex.org/keywords/resnet-50","display_name":"ResNet50","score":0.996999979019165},{"id":"https://openalex.org/keywords/sars-cov-2","display_name":"SARS-CoV-2","score":0.7689999938011169},{"id":"https://openalex.org/keywords/medical-image-classification","display_name":"medical image classification","score":0.7829999923706055}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.8682394027709961},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8281480073928833},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.7818107604980469},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7076079845428467},{"id":"https://openalex.org/C2781215313","wikidata":"https://www.wikidata.org/wiki/Q3493345","display_name":"SPARK (programming language)","level":2,"score":0.7047593593597412},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6395045518875122},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6285514831542969},{"id":"https://openalex.org/C3007834351","wikidata":"https://www.wikidata.org/wiki/Q82069695","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","level":5,"score":0.522919774055481},{"id":"https://openalex.org/C3006700255","wikidata":"https://www.wikidata.org/wiki/Q81068910","display_name":"2019-20 coronavirus outbreak","level":3,"score":0.484007328748703},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37198084592819214},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.25981390476226807},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.16324549913406372},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.14106446504592896},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C116675565","wikidata":"https://www.wikidata.org/wiki/Q3241045","display_name":"Outbreak","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3034709671","doi":null,"is_oa":false,"landing_page_url":"https://pesquisa.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/resource/en/covidwho-599056","pdf_url":null,"source":{"id":"https://openalex.org/S151779546","display_name":"Romanian Journal of Information Science and Technology","issn_l":"1453-8245","issn":["1453-8245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","norway-1","poland-20","russia-white-list-3"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Romanian Journal of Information Science and Technology","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8371999859809875,"display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3202720719","https://openalex.org/W3151238323","https://openalex.org/W3115081522","https://openalex.org/W4220876090","https://openalex.org/W3165580226","https://openalex.org/W4308440242","https://openalex.org/W7217489948","https://openalex.org/W4285791437","https://openalex.org/W4386447776","https://openalex.org/W3049070922"],"abstract_inverted_index":{"A":[0],"chest":[1,89],"X-ray":[2,39,90,109],"test":[3],"is":[4,17,41],"one":[5],"of":[6,30,36,86,107],"the":[7,18,28,51,84,105,114,122],"most":[8],"important":[9],"and":[10,61,77,118],"recurrent":[11],"medical":[12],"imaging":[13,20],"examinations":[14],"It":[16],"first":[19],"technique":[21],"that":[22,45],"represents":[23],"a":[24,42,63],"significant":[25],"role":[26],"in":[27,88,104],"diagnosis":[29],"SARS-CoV-2":[31],"disease":[32],"Automatic":[34],"classification":[35,85],"2019-nCoV":[37],"using":[38,69],"images":[40,91,110],"major":[43],"request":[44],"can":[46],"help":[47],"doctors":[48],"to":[49],"make":[50],"best":[52],"decisions":[53],"In":[55],"this":[56],"paper,":[57],"we":[58],"adopted,":[59],"developed,":[60],"validated":[62],"Deep":[64],"Transfer":[65],"Learning":[66],"(DTL)":[67],"method":[68],"Convolutional":[70],"Neural":[71],"Network":[72],"(CNN)":[73],"based":[74],"models":[75],"InceptionV3":[76,116],"ResNet50":[78,123],"with":[79],"Apache":[80],"Spark":[81],"framework":[82],"for":[83,121],"COVID-19":[87,108],"collected":[92],"from":[93],"Kaggle":[94],"repository":[95],"High":[97],"accuracy":[98],"was":[99],"obtained":[100],"by":[101,113],"our":[102],"model":[103,117,124],"detection":[106],"99":[111],"01%":[112],"pre-trained":[115],"98":[119],"03%":[120]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":5}],"updated_date":"2026-11-03T10:50:19.383937","created_date":"2020-06-19T00:00:00"}