{"id":"https://openalex.org/W3144024447","doi":"https://doi.org/10.1109/jbhi.2021.3069798","title":"Automated Detection of COVID-19 Cases on Radiographs using Shape-Dependent Fibonacci-p Patterns","display_name":"Automated Detection of COVID-19 Cases on Radiographs using Shape-Dependent Fibonacci-p Patterns","publication_year":2021,"publication_date":"2021-03-31","ids":{"openalex":"https://openalex.org/W3144024447","doi":"https://doi.org/10.1109/jbhi.2021.3069798","mag":"3144024447","pmid":"https://pubmed.ncbi.nlm.nih.gov/33788696"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2021.3069798","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jbhi.2021.3069798","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/jbhi.2021.3069798","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069074343","display_name":"Karen Panetta","orcid":"https://orcid.org/0000-0001-9435-4536"},"institutions":[{"id":"https://openalex.org/I121934306","display_name":"Tufts University","ror":"https://ror.org/05wvpxv85","country_code":"US","type":"education","lineage":["https://openalex.org/I121934306"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karen Panetta","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Tufts University, Medford, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Tufts University, Medford, MA, USA","institution_ids":["https://openalex.org/I121934306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048627000","display_name":"Foram M. Sanghavi","orcid":"https://orcid.org/0000-0002-2334-7053"},"institutions":[{"id":"https://openalex.org/I121934306","display_name":"Tufts University","ror":"https://ror.org/05wvpxv85","country_code":"US","type":"education","lineage":["https://openalex.org/I121934306"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Foram Sanghavi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Tufts University, Medford, MA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2334-7053","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Tufts University, Medford, MA, USA","institution_ids":["https://openalex.org/I121934306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048285657","display_name":"Sos \u0421. Agaian","orcid":"https://orcid.org/0000-0003-4601-4507"},"institutions":[{"id":"https://openalex.org/I174216632","display_name":"City University of New York","ror":"https://ror.org/00453a208","country_code":"US","type":"education","lineage":["https://openalex.org/I174216632"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sos Agaian","raw_affiliation_strings":["Department of Computer Science, City University of New York, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-4601-4507","affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of New York, New York, NY, USA","institution_ids":["https://openalex.org/I174216632"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062263876","display_name":"Neel Madan","orcid":"https://orcid.org/0000-0002-3889-7293"},"institutions":[{"id":"https://openalex.org/I1290900354","display_name":"Tufts Medical Center","ror":"https://ror.org/002hsbm82","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1290900354"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neel Madan","raw_affiliation_strings":["Department of Radiology, Tufts Medical Center, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Tufts Medical Center, Boston, MA, USA","institution_ids":["https://openalex.org/I1290900354"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.5009,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.95107443,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"25","issue":"6","first_page":"1852","last_page":"1863"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9732000231742859,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9692999720573425,"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/radiography","display_name":"Radiography","score":0.7484838962554932},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6371562480926514},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6074275970458984},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.5869728326797485},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5123113393783569},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4659861922264099},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.44536933302879333},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4360000193119049},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43071573972702026},{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.4291520416736603},{"id":"https://openalex.org/keywords/chest-radiograph","display_name":"Chest radiograph","score":0.4164227843284607},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41163045167922974},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3728443384170532},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3615441918373108},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.19940191507339478},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.13870185613632202}],"concepts":[{"id":"https://openalex.org/C36454342","wikidata":"https://www.wikidata.org/wiki/Q245341","display_name":"Radiography","level":2,"score":0.7484838962554932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6371562480926514},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6074275970458984},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.5869728326797485},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5123113393783569},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4659861922264099},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.44536933302879333},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4360000193119049},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43071573972702026},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.4291520416736603},{"id":"https://openalex.org/C2781137159","wikidata":"https://www.wikidata.org/wiki/Q1283318","display_name":"Chest radiograph","level":3,"score":0.4164227843284607},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41163045167922974},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3728443384170532},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3615441918373108},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.19940191507339478},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.13870185613632202},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000821","qualifier_name":"virology","is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000821","qualifier_name":"virology","is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000821","qualifier_name":"virology","is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":"Q000302","qualifier_name":"isolation & purification","is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":"Q000302","qualifier_name":"isolation & purification","is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":"Q000302","qualifier_name":"isolation & purification","is_major_topic":false},{"descriptor_ui":"D001331","descriptor_name":"Automation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001331","descriptor_name":"Automation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001331","descriptor_name":"Automation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":"Q000821","qualifier_name":"virology","is_major_topic":false},{"descriptor_ui":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":"Q000821","qualifier_name":"virology","is_major_topic":false},{"descriptor_ui":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":"Q000821","qualifier_name":"virology","is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/jbhi.2021.3069798","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jbhi.2021.3069798","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:33788696","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33788696","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE journal of biomedical and health informatics","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:8768975","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8768975","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"IEEE J Biomed Health Inform","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1109/jbhi.2021.3069798","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jbhi.2021.3069798","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8700000047683716,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1843749293","https://openalex.org/W1968969471","https://openalex.org/W1970014886","https://openalex.org/W2034958235","https://openalex.org/W2070493638","https://openalex.org/W2087347434","https://openalex.org/W2088252378","https://openalex.org/W2096171208","https://openalex.org/W2116620640","https://openalex.org/W2125283600","https://openalex.org/W2147595228","https://openalex.org/W2155632266","https://openalex.org/W2615996824","https://openalex.org/W2758040203","https://openalex.org/W2884345610","https://openalex.org/W2914550345","https://openalex.org/W2949308781","https://openalex.org/W2952649530","https://openalex.org/W3001118548","https://openalex.org/W3001195213","https://openalex.org/W3002108456","https://openalex.org/W3003637715","https://openalex.org/W3003668884","https://openalex.org/W3004906315","https://openalex.org/W3005030567","https://openalex.org/W3005079553","https://openalex.org/W3005580744","https://openalex.org/W3006082171","https://openalex.org/W3007497549","https://openalex.org/W3007764760","https://openalex.org/W3007964452","https://openalex.org/W3008985036","https://openalex.org/W3010604545","https://openalex.org/W3012211282","https://openalex.org/W3013019084","https://openalex.org/W3013277995","https://openalex.org/W3013564598","https://openalex.org/W3013601031","https://openalex.org/W3014322576","https://openalex.org/W3017744567","https://openalex.org/W3017855299","https://openalex.org/W3021001507","https://openalex.org/W3022719712","https://openalex.org/W3085482309","https://openalex.org/W3104951425","https://openalex.org/W3105081694","https://openalex.org/W3114166611","https://openalex.org/W3140022118","https://openalex.org/W3158317643","https://openalex.org/W3162351260","https://openalex.org/W3165656738","https://openalex.org/W6738039341","https://openalex.org/W6773574953","https://openalex.org/W6774326982","https://openalex.org/W6775352234","https://openalex.org/W6775513650","https://openalex.org/W6776129192","https://openalex.org/W6792048891","https://openalex.org/W6795304270"],"related_works":["https://openalex.org/W2023863717","https://openalex.org/W2334498971","https://openalex.org/W2140868683","https://openalex.org/W4313585012","https://openalex.org/W2991131751","https://openalex.org/W2358294942","https://openalex.org/W2328406146","https://openalex.org/W2743522447","https://openalex.org/W2181826856","https://openalex.org/W2019414200"],"abstract_inverted_index":{"The":[0],"coronavirus":[1],"(COVID-19)":[2],"pandemic":[3],"has":[4,114],"been":[5],"adversely":[6],"affecting":[7],"people's":[8],"health":[9],"globally.":[10],"To":[11,144],"diminish":[12],"the":[13,91,96,136,141,146,149,176,181,201],"effect":[14],"of":[15,98,148,188,194],"this":[16,71],"widespread":[17],"pandemic,":[18],"it":[19],"is":[20,85,107,173,198],"essential":[21],"to":[22,119],"detect":[23],"COVID-19":[24,66,171],"cases":[25],"as":[26,28,156],"quickly":[27],"possible.":[29],"Chest":[30],"radiographs":[31,172],"are":[32,36,128,163],"less":[33],"expensive":[34],"and":[35,58,103,112,139,161,170,192],"a":[37,52,73,81],"widely":[38],"available":[39,133],"imaging":[40],"modality":[41],"for":[42,62,175,200],"detecting":[43],"chest":[44,67],"pathology":[45],"compared":[46,118],"with":[47,123],"CT":[48],"images.":[49],"They":[50],"play":[51],"vital":[53],"role":[54],"in":[55],"early":[56],"prediction":[57],"developing":[59],"treatment":[60],"plans":[61],"suspected":[63],"or":[64],"confirmed":[65],"infection":[68],"patients.":[69],"In":[70],"paper,":[72],"novel":[74],"shape-dependent":[75],"Fibonacci-p":[76],"patterns-based":[77],"feature":[78],"descriptor":[79],"using":[80,180],"machine":[82],"learning":[83,121],"approach":[84],"proposed.":[86],"Computer":[87,126],"simulations":[88,127],"show":[89],"that":[90],"presented":[92,150],"system":[93],"(1)":[94],"increases":[95],"effectiveness":[97],"differentiating":[99],"COVID-19,":[100],"viral":[101],"pneumonia,":[102],"normal":[104,169],"conditions,":[105],"(2)":[106],"effective":[108],"on":[109,130],"small":[110],"datasets,":[111],"(3)":[113],"faster":[115],"inference":[116],"time":[117],"deep":[120],"methods":[122],"comparable":[124],"performance.":[125],"performed":[129],"two":[131],"publicly":[132],"datasets;":[134],"(a)":[135],"Kaggle":[137,184],"dataset,":[138],"(b)":[140],"COVIDGR":[142,202],"dataset.":[143,203],"assess":[145],"performance":[147],"system,":[151],"various":[152],"evaluation":[153],"parameters,":[154],"such":[155],"accuracy,":[157],"recall,":[158],"specificity,":[159],"precision,":[160],"f1-score":[162],"used.":[164],"Nearly":[165],"100%":[166],"differentiation":[167],"between":[168],"observed":[174,199],"three-class":[177],"classification":[178],"scheme":[179],"lung":[182],"area-specific":[183],"radiographs.":[185],"While":[186],"Recall":[187],"72.65":[189],"\u00b1":[190,196],"6.83":[191],"specificity":[193],"77.72":[195],"8.06":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2021-04-13T00:00:00"}