{"id":"https://openalex.org/W4210473780","doi":"https://doi.org/10.1080/08839514.2022.2033473","title":"A Novel Data Augmentation Convolutional Neural Network for Detecting Malaria Parasite in Blood Smear Images","display_name":"A Novel Data Augmentation Convolutional Neural Network for Detecting Malaria Parasite in Blood Smear Images","publication_year":2022,"publication_date":"2022-01-25","ids":{"openalex":"https://openalex.org/W4210473780","doi":"https://doi.org/10.1080/08839514.2022.2033473"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2022.2033473","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2033473","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2033473?needAccess=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2033473?needAccess=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007021582","display_name":"David Opeoluwa Oyewola","orcid":"https://orcid.org/0000-0001-9638-8764"},"institutions":[{"id":"https://openalex.org/I4210148832","display_name":"Federal University Kashere","ror":"https://ror.org/0470nf974","country_code":"NG","type":"education","lineage":["https://openalex.org/I4210148832"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"David Opeoluwa Oyewola","raw_affiliation_strings":["Department of Mathematics and Computer Science, Federal University Kashere, Gombe, Nigeria"],"raw_orcid":"https://orcid.org/0000-0001-9638-8764","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, Federal University Kashere, Gombe, Nigeria","institution_ids":["https://openalex.org/I4210148832"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022712723","display_name":"Emmanuel Gbenga Dada","orcid":"https://orcid.org/0000-0002-1132-5447"},"institutions":[{"id":"https://openalex.org/I64351976","display_name":"University of Maiduguri","ror":"https://ror.org/016na8197","country_code":"NG","type":"education","lineage":["https://openalex.org/I64351976"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Emmanuel Gbenga Dada","raw_affiliation_strings":["Department of Mathematical Sciences, University of Maiduguri, Maiduguri, Nigeria"],"raw_orcid":"https://orcid.org/0000-0002-1132-5447","affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, University of Maiduguri, Maiduguri, Nigeria","institution_ids":["https://openalex.org/I64351976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064136287","display_name":"Sanjay Misra","orcid":"https://orcid.org/0000-0002-3556-9331"},"institutions":[{"id":"https://openalex.org/I19923696","display_name":"\u00d8stfold University College","ror":"https://ror.org/04gf7fp41","country_code":"NO","type":"education","lineage":["https://openalex.org/I19923696"]}],"countries":["NO"],"is_corresponding":true,"raw_author_name":"Sanjay Misra","raw_affiliation_strings":["Department of Computer Science and Communication, \u00d8stfold University College, Halden, Norway"],"raw_orcid":"https://orcid.org/0000-0002-3556-9331","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Communication, \u00d8stfold University College, Halden, Norway","institution_ids":["https://openalex.org/I19923696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042653526","display_name":"Robertas Dama\u0161evi\u010dius","orcid":"https://orcid.org/0000-0001-9990-1084"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Robertas Dama\u0161evi\u010dius","raw_affiliation_strings":["Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland"],"raw_orcid":"https://orcid.org/0000-0001-9990-1084","affiliations":[{"raw_affiliation_string":"Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5064136287"],"corresponding_institution_ids":["https://openalex.org/I19923696"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":{"value":2195,"currency":"USD","value_usd":2195},"fwci":6.7063,"has_fulltext":false,"cited_by_count":68,"citation_normalized_percentile":{"value":0.97805225,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"36","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":1.0,"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"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9878000020980835,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9779999852180481,"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/malaria","display_name":"Malaria","score":0.9166322946548462},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7588076591491699},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7267582416534424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6995868682861328},{"id":"https://openalex.org/keywords/blood-smear","display_name":"Blood smear","score":0.6372331976890564},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4760969877243042},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43936580419540405},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3752100467681885},{"id":"https://openalex.org/keywords/immunology","display_name":"Immunology","score":0.23833060264587402},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.15815746784210205}],"concepts":[{"id":"https://openalex.org/C2778048844","wikidata":"https://www.wikidata.org/wiki/Q12156","display_name":"Malaria","level":2,"score":0.9166322946548462},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7588076591491699},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7267582416534424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6995868682861328},{"id":"https://openalex.org/C3017819844","wikidata":"https://www.wikidata.org/wiki/Q886475","display_name":"Blood smear","level":3,"score":0.6372331976890564},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4760969877243042},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43936580419540405},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3752100467681885},{"id":"https://openalex.org/C203014093","wikidata":"https://www.wikidata.org/wiki/Q101929","display_name":"Immunology","level":1,"score":0.23833060264587402},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.15815746784210205}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/08839514.2022.2033473","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2033473","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2033473?needAccess=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:72b96291869445e4ae1385b5c201390f","is_oa":false,"landing_page_url":"https://doaj.org/article/72b96291869445e4ae1385b5c201390f","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 36, Iss 1 (2022)","raw_type":"article"},{"id":"pmh:oai:hiof.brage.unit.no:11250/3032526","is_oa":true,"landing_page_url":"https://hdl.handle.net/11250/3032526","pdf_url":null,"source":{"id":"https://openalex.org/S4306401716","display_name":"Duo Research Archive (University of Oslo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184942183","host_organization_name":"University of Oslo","host_organization_lineage":["https://openalex.org/I184942183"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"36","raw_type":"info:eu-repo/semantics/other"}],"best_oa_location":{"id":"doi:10.1080/08839514.2022.2033473","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2033473","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2033473?needAccess=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8399999737739563,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4210473780.pdf","grobid_xml":"https://content.openalex.org/works/W4210473780.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1980712697","https://openalex.org/W1996961232","https://openalex.org/W2062205667","https://openalex.org/W2071354075","https://openalex.org/W2097117768","https://openalex.org/W2194775991","https://openalex.org/W2592929672","https://openalex.org/W2610332124","https://openalex.org/W2617959447","https://openalex.org/W2741016737","https://openalex.org/W2768956845","https://openalex.org/W2783699776","https://openalex.org/W2790685217","https://openalex.org/W2807263159","https://openalex.org/W2891868672","https://openalex.org/W2914821433","https://openalex.org/W2917059200","https://openalex.org/W2919115771","https://openalex.org/W2919358988","https://openalex.org/W2947621394","https://openalex.org/W2947946667","https://openalex.org/W2954996726","https://openalex.org/W2977373448","https://openalex.org/W2981038142","https://openalex.org/W2981560029","https://openalex.org/W2986426091","https://openalex.org/W2995942064","https://openalex.org/W2996935211","https://openalex.org/W2999209878","https://openalex.org/W3013339876","https://openalex.org/W3027051205","https://openalex.org/W3036871615","https://openalex.org/W3041038332","https://openalex.org/W3093426589","https://openalex.org/W3134437630","https://openalex.org/W3135361473","https://openalex.org/W3156482429","https://openalex.org/W3166253025","https://openalex.org/W3172943905","https://openalex.org/W3173873057","https://openalex.org/W3179013378","https://openalex.org/W3208239477","https://openalex.org/W3213222106"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W2606416966","https://openalex.org/W3117607624","https://openalex.org/W4210817158"],"abstract_inverted_index":{"Malaria":[0],"fever":[1,23],"is":[2,117],"a":[3,89,95],"potentially":[4],"fatal":[5],"disease":[6],"caused":[7],"by":[8,103],"the":[9,29,82,113,158,171],"Plasmodium":[10,13],"parasite.":[11],"Identifying":[12],"parasites":[14,175],"in":[15,45,58,61,137,147,176],"blood":[16,149,177],"smear":[17,178],"images":[18,151],"can":[19,164],"help":[20],"diagnose":[21],"malaria":[22,38,50,55,78,148,174],"rapidly":[24],"and":[25,40,52,121,139],"precisely.":[26],"According":[27],"to":[28,106],"World":[30],"Health":[31],"Organization":[32],"(WHO),":[33],"there":[34],"were":[35],"241":[36],"million":[37],"cases":[39,51],"627":[41],"000":[42],"deaths":[43,56],"worldwide":[44],"2020,":[46],"while":[47],"95%":[48],"of":[49,54,76,84,112,152,173],"96%":[53],"occurred":[57],"Africa.":[59],"Also":[60],"Africa,":[62],"children":[63],"that":[64,132],"are":[65],"less":[66],"than":[67],"five":[68],"years":[69],"old":[70],"accounted":[71],"for":[72,170],"an":[73,167],"estimated":[74],"80%":[75],"all":[77],"deaths.":[79],"To":[80],"address":[81],"menace":[83],"malaria,":[85],"this":[86,108],"paper":[87],"proposes":[88],"novel":[90],"deep":[91],"learning":[92,105],"model,":[93],"called":[94],"data":[96],"augmentation":[97],"convolutional":[98,125],"neural":[99,126],"network":[100,127],"(DACNN),":[101],"trained":[102],"reinforcement":[104],"tackle":[107],"problem.":[109],"The":[110,161],"performance":[111],"proposed":[114,162],"DACNN":[115,133],"model":[116,163],"compared":[118],"with":[119],"CNN":[120],"directed":[122],"acyclic":[123],"graph":[124],"(DAGCNN)":[128],"models.":[129],"Results":[130],"show":[131],"outperforms":[134],"previous":[135],"studies":[136],"processing":[138],"classification":[140,145],"images.":[141,179],"It":[142],"achieved":[143],"94.79%":[144],"accuracy":[146],"sample":[150],"balanced":[153],"class":[154],"dataset":[155],"obtained":[156],"from":[157],"Kaggle":[159],"dataset.":[160],"serve":[165],"as":[166],"effective":[168],"tool":[169],"detection":[172]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":17}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}