{"id":"https://openalex.org/W4213443174","doi":"https://doi.org/10.1007/s11227-022-04349-y","title":"Exploiting probability density function of deep convolutional autoencoders\u2019 latent space for reliable COVID-19 detection on CT scans","display_name":"Exploiting probability density function of deep convolutional autoencoders\u2019 latent space for reliable COVID-19 detection on CT scans","publication_year":2022,"publication_date":"2022-02-24","ids":{"openalex":"https://openalex.org/W4213443174","doi":"https://doi.org/10.1007/s11227-022-04349-y","pmid":"https://pubmed.ncbi.nlm.nih.gov/35228777"},"language":"en","primary_location":{"id":"doi:10.1007/s11227-022-04349-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11227-022-04349-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11227-022-04349-y.pdf","source":{"id":"https://openalex.org/S32326811","display_name":"The Journal of Supercomputing","issn_l":"0920-8542","issn":["0920-8542","1573-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of Supercomputing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11227-022-04349-y.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084337425","display_name":"Sima Sarv Ahrabi","orcid":"https://orcid.org/0000-0001-8379-8799"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Sima Sarv Ahrabi","raw_affiliation_strings":["Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184 Roma, Italy","Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184, Roma, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184 Roma, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184, Roma, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081554435","display_name":"Lorenzo Piazzo","orcid":"https://orcid.org/0000-0002-5325-8561"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Lorenzo Piazzo","raw_affiliation_strings":["Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184 Roma, Italy","Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184, Roma, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184 Roma, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184, Roma, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052744478","display_name":"Alireza Momenzadeh","orcid":"https://orcid.org/0000-0002-5682-4186"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alireza Momenzadeh","raw_affiliation_strings":["Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184 Roma, Italy","Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184, Roma, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184 Roma, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184, Roma, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067809229","display_name":"Michele Scarpiniti","orcid":"https://orcid.org/0000-0002-3164-6256"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Michele Scarpiniti","raw_affiliation_strings":["Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184 Roma, Italy","Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184, Roma, Italy"],"raw_orcid":"https://orcid.org/0000-0002-3164-6256","affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184 Roma, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184, Roma, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020320957","display_name":"Enzo Baccarelli","orcid":"https://orcid.org/0000-0002-9791-7901"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Enzo Baccarelli","raw_affiliation_strings":["Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184 Roma, Italy","Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184, Roma, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184 Roma, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Via Eudossiana 18, 00184, Roma, Italy","institution_ids":["https://openalex.org/I861853513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5084337425"],"corresponding_institution_ids":["https://openalex.org/I861853513"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.0306,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.74045136,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"78","issue":"9","first_page":"12024","last_page":"12045"},"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":0.9921000003814697,"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":0.9819999933242798,"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/autoencoder","display_name":"Autoencoder","score":0.8332579731941223},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.797393798828125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7241598963737488},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.683998167514801},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6016632318496704},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5635839104652405},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5562595129013062},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.5401732921600342},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5400986671447754},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.53546541929245},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.530971884727478},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5285602807998657},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.5151902437210083},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.47689250111579895},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46055591106414795},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4293852150440216},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.42338353395462036},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3759292960166931},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14267167448997498},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13040831685066223}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8332579731941223},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.797393798828125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7241598963737488},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.683998167514801},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6016632318496704},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5635839104652405},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5562595129013062},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5401732921600342},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5400986671447754},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.53546541929245},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.530971884727478},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5285602807998657},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.5151902437210083},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.47689250111579895},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46055591106414795},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4293852150440216},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.42338353395462036},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3759292960166931},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14267167448997498},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13040831685066223},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s11227-022-04349-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11227-022-04349-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11227-022-04349-y.pdf","source":{"id":"https://openalex.org/S32326811","display_name":"The Journal of Supercomputing","issn_l":"0920-8542","issn":["0920-8542","1573-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of Supercomputing","raw_type":"journal-article"},{"id":"pmid:35228777","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35228777","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":"The Journal of supercomputing","raw_type":null},{"id":"pmh:oai:iris.uniroma1.it:11573/1650358","is_oa":true,"landing_page_url":"https://hdl.handle.net/11573/1650358","pdf_url":null,"source":{"id":"https://openalex.org/S4377196107","display_name":"IRIS Research product catalog (Sapienza University of Rome)","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:pubmedcentral.nih.gov:8867464","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8867464","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":"J Supercomput","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s11227-022-04349-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11227-022-04349-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11227-022-04349-y.pdf","source":{"id":"https://openalex.org/S32326811","display_name":"The Journal of Supercomputing","issn_l":"0920-8542","issn":["0920-8542","1573-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of Supercomputing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4683936200","display_name":null,"funder_award_id":"RM11816426B7A216","funder_id":"https://openalex.org/F4320322510","funder_display_name":"Sapienza Universit\u00e0 di Roma"},{"id":"https://openalex.org/G4835134179","display_name":null,"funder_award_id":"RM11916B323CE30C","funder_id":"https://openalex.org/F4320311825","funder_display_name":"Facolt\u00e0 di Medicina e Psicologiaa, Sapienza Universit\u00e0 di Roma"},{"id":"https://openalex.org/G5844914927","display_name":null,"funder_award_id":"MA21816436AA4280","funder_id":"https://openalex.org/F4320322510","funder_display_name":"Sapienza Universit\u00e0 di Roma"},{"id":"https://openalex.org/G8858457790","display_name":null,"funder_award_id":"RM12017294171495","funder_id":"https://openalex.org/F4320322510","funder_display_name":"Sapienza Universit\u00e0 di Roma"}],"funders":[{"id":"https://openalex.org/F4320311825","display_name":"Facolt\u00e0 di Medicina e Psicologiaa, Sapienza Universit\u00e0 di Roma","ror":"https://ror.org/02be6w209"},{"id":"https://openalex.org/F4320322510","display_name":"Sapienza Universit\u00e0 di Roma","ror":"https://ror.org/02be6w209"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4213443174.pdf","grobid_xml":"https://content.openalex.org/works/W4213443174.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W638544165","https://openalex.org/W1999862258","https://openalex.org/W2042574171","https://openalex.org/W2097117768","https://openalex.org/W2100530741","https://openalex.org/W2136655611","https://openalex.org/W2146777870","https://openalex.org/W2194775991","https://openalex.org/W2561966715","https://openalex.org/W3006110666","https://openalex.org/W3007497549","https://openalex.org/W3008985036","https://openalex.org/W3012857944","https://openalex.org/W3015836412","https://openalex.org/W3016292699","https://openalex.org/W3017644243","https://openalex.org/W3019449959","https://openalex.org/W3036638392","https://openalex.org/W3041148517","https://openalex.org/W3090231249","https://openalex.org/W3091940685","https://openalex.org/W3094388274","https://openalex.org/W3095676075","https://openalex.org/W3101606529","https://openalex.org/W3105081694","https://openalex.org/W3106794539","https://openalex.org/W3114166611","https://openalex.org/W3119875393","https://openalex.org/W3120531891","https://openalex.org/W3126240305","https://openalex.org/W3126486492","https://openalex.org/W3126684630","https://openalex.org/W3128580531","https://openalex.org/W3133191822","https://openalex.org/W3133262691","https://openalex.org/W3135243128","https://openalex.org/W3135531566","https://openalex.org/W3139833881","https://openalex.org/W3144777302","https://openalex.org/W3156342878","https://openalex.org/W3164076340","https://openalex.org/W3171963620","https://openalex.org/W3174805961","https://openalex.org/W3196703073","https://openalex.org/W3199810304","https://openalex.org/W3203975471","https://openalex.org/W4200161740"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W2028462208","https://openalex.org/W4285337533","https://openalex.org/W2982831492","https://openalex.org/W3138055416","https://openalex.org/W3094735304","https://openalex.org/W2187490799","https://openalex.org/W1574942924","https://openalex.org/W2900267584","https://openalex.org/W3019226033"],"abstract_inverted_index":{"Abstract":[0],"We":[1,155],"present":[2],"a":[3,28,34,104,142],"probabilistic":[4],"method":[5],"for":[6],"classifying":[7],"chest":[8],"computed":[9],"tomography":[10],"(CT)":[11],"scans":[12],"into":[13,107],"COVID-19":[14,44,147],"and":[15,22,118,164],"non-COVID-19.":[16],"To":[17],"this":[18,136],"end,":[19],"we":[20,70,102,120],"design":[21],"train,":[23],"in":[24,98],"an":[25],"unsupervised":[26],"manner,":[27],"deep":[29],"convolutional":[30],"autoencoder":[31],"(DCAE)":[32],"on":[33],"selected":[35],"training":[36,66,87,165],"data":[37,67,88],"set,":[38],"which":[39],"is":[40,50,139],"composed":[41],"only":[42],"of":[43,64,85,92,131,172],"CT":[45,106],"scans.":[46],"Once":[47],"the":[48,52,56,65,72,79,86,99,108,113,122,127,132,146,152],"model":[49],"trained,":[51],"encoder":[53,110],"can":[54],"generate":[55],"compact":[57],"hidden":[58,61,74,115],"representation":[59,75],"(the":[60],"feature":[62,116],"vectors)":[63],"set.":[68],"Afterwards,":[69],"exploit":[71],"obtained":[73,137],"to":[76,111,125,141,144,151],"build":[77],"up":[78],"target":[80,123],"probability":[81],"density":[82,94],"function":[83],"(PDF)":[84],"set":[89],"by":[90,167],"means":[91],"kernel":[93],"estimation":[95],"(KDE).":[96],"Subsequently,":[97],"test":[100,105,133,153,162],"phase,":[101],"feed":[103],"trained":[109],"produce":[112],"corresponding":[114,128],"vector,":[117],"then,":[119],"utilise":[121],"PDF":[124,129],"compute":[126],"value":[130,138],"image.":[134,154],"Finally,":[135],"compared":[140],"threshold":[143],"assign":[145],"label":[148],"or":[149],"non-COVID-19":[150],"numerically":[156],"check":[157],"our":[158],"approach\u2019s":[159],"performance":[160],"(i.e.":[161],"accuracy":[163],"times)":[166],"comparing":[168],"it":[169],"with":[170],"those":[171],"some":[173],"state-of-the-art":[174],"methods.":[175]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4}],"updated_date":"2026-05-16T08:24:45.110214","created_date":"2022-02-25T00:00:00"}
