{"id":"https://openalex.org/W4387296111","doi":"https://doi.org/10.1007/s10278-023-00897-8","title":"Bayesian Convolutional Neural Networks in Medical Imaging Classification: A Promising Solution for Deep Learning Limits in Data Scarcity Scenarios","display_name":"Bayesian Convolutional Neural Networks in Medical Imaging Classification: A Promising Solution for Deep Learning Limits in Data Scarcity Scenarios","publication_year":2023,"publication_date":"2023-10-03","ids":{"openalex":"https://openalex.org/W4387296111","doi":"https://doi.org/10.1007/s10278-023-00897-8","pmid":"https://pubmed.ncbi.nlm.nih.gov/37787869"},"language":"en","primary_location":{"id":"doi:10.1007/s10278-023-00897-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-023-00897-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-023-00897-8.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Digital Imaging","issn_l":"0897-1889","issn":["0897-1889","1618-727X"],"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":"Journal of Digital Imaging","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/s10278-023-00897-8.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092991727","display_name":"Filippo Bargagna","orcid":"https://orcid.org/0009-0006-6403-0585"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]},{"id":"https://openalex.org/I4210158339","display_name":"Fondazione Toscana Gabriele Monasterio","ror":"https://ror.org/058a2pj71","country_code":"IT","type":"other","lineage":["https://openalex.org/I4210155236","https://openalex.org/I4210158339"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Filippo Bargagna","raw_affiliation_strings":["Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy. filippo.bargagna@phd.unipi.it","University of Pisa, Pisa, Italy. filippo.bargagna@phd.unipi.it","University of Pisa, Pisa, Italy"],"raw_orcid":"https://orcid.org/0009-0006-6403-0585","affiliations":[{"raw_affiliation_string":"Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy. filippo.bargagna@phd.unipi.it","institution_ids":["https://openalex.org/I4210158339"]},{"raw_affiliation_string":"University of Pisa, Pisa, Italy. filippo.bargagna@phd.unipi.it","institution_ids":["https://openalex.org/I108290504"]},{"raw_affiliation_string":"University of Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076728110","display_name":"Lisa Anita De Santi","orcid":"https://orcid.org/0000-0001-7239-4270"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]},{"id":"https://openalex.org/I4210158339","display_name":"Fondazione Toscana Gabriele Monasterio","ror":"https://ror.org/058a2pj71","country_code":"IT","type":"other","lineage":["https://openalex.org/I4210155236","https://openalex.org/I4210158339"]},{"id":"https://openalex.org/I4387153402","display_name":"Regione Toscana","ror":"https://ror.org/02r6c6d62","country_code":null,"type":"government","lineage":["https://openalex.org/I4387153402"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Lisa Anita De Santi","raw_affiliation_strings":["Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy","University of Pisa, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy","institution_ids":["https://openalex.org/I4210158339","https://openalex.org/I4387153402"]},{"raw_affiliation_string":"University of Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006232447","display_name":"Nicola Martini","orcid":"https://orcid.org/0000-0003-3008-0163"},"institutions":[{"id":"https://openalex.org/I4210158339","display_name":"Fondazione Toscana Gabriele Monasterio","ror":"https://ror.org/058a2pj71","country_code":"IT","type":"other","lineage":["https://openalex.org/I4210155236","https://openalex.org/I4210158339"]},{"id":"https://openalex.org/I4387153402","display_name":"Regione Toscana","ror":"https://ror.org/02r6c6d62","country_code":null,"type":"government","lineage":["https://openalex.org/I4387153402"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nicola Martini","raw_affiliation_strings":["Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy","institution_ids":["https://openalex.org/I4210158339","https://openalex.org/I4387153402"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041082156","display_name":"Dario Genovesi","orcid":"https://orcid.org/0000-0002-8958-4385"},"institutions":[{"id":"https://openalex.org/I4210158339","display_name":"Fondazione Toscana Gabriele Monasterio","ror":"https://ror.org/058a2pj71","country_code":"IT","type":"other","lineage":["https://openalex.org/I4210155236","https://openalex.org/I4210158339"]},{"id":"https://openalex.org/I4387153402","display_name":"Regione Toscana","ror":"https://ror.org/02r6c6d62","country_code":null,"type":"government","lineage":["https://openalex.org/I4387153402"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Dario Genovesi","raw_affiliation_strings":["Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy","institution_ids":["https://openalex.org/I4210158339","https://openalex.org/I4387153402"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075027274","display_name":"Brunella Favilli","orcid":null},"institutions":[{"id":"https://openalex.org/I4210158339","display_name":"Fondazione Toscana Gabriele Monasterio","ror":"https://ror.org/058a2pj71","country_code":"IT","type":"other","lineage":["https://openalex.org/I4210155236","https://openalex.org/I4210158339"]},{"id":"https://openalex.org/I4387153402","display_name":"Regione Toscana","ror":"https://ror.org/02r6c6d62","country_code":null,"type":"government","lineage":["https://openalex.org/I4387153402"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Brunella Favilli","raw_affiliation_strings":["Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy","institution_ids":["https://openalex.org/I4210158339","https://openalex.org/I4387153402"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035769119","display_name":"Giuseppe Vergaro","orcid":"https://orcid.org/0000-0002-7066-6006"},"institutions":[{"id":"https://openalex.org/I162290304","display_name":"Scuola Superiore Sant'Anna","ror":"https://ror.org/025602r80","country_code":"IT","type":"education","lineage":["https://openalex.org/I162290304"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giuseppe Vergaro","raw_affiliation_strings":["Scuola Universitaria Superiore 'S. Anna', Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Scuola Universitaria Superiore 'S. Anna', Pisa, Italy","institution_ids":["https://openalex.org/I162290304"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024386124","display_name":"Michele Emdin","orcid":"https://orcid.org/0000-0002-8541-1962"},"institutions":[{"id":"https://openalex.org/I162290304","display_name":"Scuola Superiore Sant'Anna","ror":"https://ror.org/025602r80","country_code":"IT","type":"education","lineage":["https://openalex.org/I162290304"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Michele Emdin","raw_affiliation_strings":["Scuola Universitaria Superiore 'S. Anna', Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Scuola Universitaria Superiore 'S. Anna', Pisa, Italy","institution_ids":["https://openalex.org/I162290304"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016571029","display_name":"Assuero Giorgetti","orcid":"https://orcid.org/0000-0001-5016-3826"},"institutions":[{"id":"https://openalex.org/I4210158339","display_name":"Fondazione Toscana Gabriele Monasterio","ror":"https://ror.org/058a2pj71","country_code":"IT","type":"other","lineage":["https://openalex.org/I4210155236","https://openalex.org/I4210158339"]},{"id":"https://openalex.org/I4387153402","display_name":"Regione Toscana","ror":"https://ror.org/02r6c6d62","country_code":null,"type":"government","lineage":["https://openalex.org/I4387153402"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Assuero Giorgetti","raw_affiliation_strings":["Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy","institution_ids":["https://openalex.org/I4210158339","https://openalex.org/I4387153402"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090506270","display_name":"Vincenzo Positano","orcid":"https://orcid.org/0000-0001-6955-9572"},"institutions":[{"id":"https://openalex.org/I4210158339","display_name":"Fondazione Toscana Gabriele Monasterio","ror":"https://ror.org/058a2pj71","country_code":"IT","type":"other","lineage":["https://openalex.org/I4210155236","https://openalex.org/I4210158339"]},{"id":"https://openalex.org/I4387153402","display_name":"Regione Toscana","ror":"https://ror.org/02r6c6d62","country_code":null,"type":"government","lineage":["https://openalex.org/I4387153402"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Vincenzo Positano","raw_affiliation_strings":["Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fondazione G. Monasterio CNR - Regione Toscana, Pisa, Italy","institution_ids":["https://openalex.org/I4210158339","https://openalex.org/I4387153402"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044785782","display_name":"Maria Filomena Santarelli","orcid":"https://orcid.org/0000-0001-8332-7006"},"institutions":[{"id":"https://openalex.org/I4210106076","display_name":"Istituto di Fisiologia Clinica","ror":"https://ror.org/01kdj2848","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210106076","https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Maria Filomena Santarelli","raw_affiliation_strings":["CNR Institute of Clinical Physiology, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNR Institute of Clinical Physiology, Pisa, Italy","institution_ids":["https://openalex.org/I4210106076"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5092991727"],"corresponding_institution_ids":["https://openalex.org/I108290504","https://openalex.org/I4210158339"],"apc_list":{"value":3190,"currency":"EUR","value_usd":4190},"apc_paid":{"value":3190,"currency":"EUR","value_usd":4190},"fwci":3.1297,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.92052442,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"36","issue":"6","first_page":"2567","last_page":"2577"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11305","display_name":"Amyloidosis: Diagnosis, Treatment, Outcomes","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11305","display_name":"Amyloidosis: Diagnosis, Treatment, Outcomes","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9314000010490417,"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/T11642","display_name":"Genomics and Rare Diseases","score":0.9190000295639038,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.789027988910675},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7243615984916687},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7164071798324585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6905407309532166},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6578112840652466},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6483241319656372},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4838939607143402},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4363408088684082},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.42018622159957886},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3615758717060089}],"concepts":[{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.789027988910675},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7243615984916687},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7164071798324585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6905407309532166},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6578112840652466},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6483241319656372},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4838939607143402},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4363408088684082},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.42018622159957886},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3615758717060089},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","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":"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":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1007/s10278-023-00897-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-023-00897-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-023-00897-8.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Digital Imaging","issn_l":"0897-1889","issn":["0897-1889","1618-727X"],"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":"Journal of Digital Imaging","raw_type":"journal-article"},{"id":"pmid:37787869","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37787869","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":"Journal of digital imaging","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10584795","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10584795","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10584795/pdf/10278_2023_Article_897.pdf","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 Digit Imaging","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s10278-023-00897-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-023-00897-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-023-00897-8.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Digital Imaging","issn_l":"0897-1889","issn":["0897-1889","1618-727X"],"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":"Journal of Digital Imaging","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.47999998927116394}],"awards":[],"funders":[{"id":"https://openalex.org/F4320324499","display_name":"Universit\u00e0 di Pisa","ror":"https://ror.org/03ad39j10"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387296111.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1826234144","https://openalex.org/W2010267169","https://openalex.org/W2085281262","https://openalex.org/W2095705004","https://openalex.org/W2116540833","https://openalex.org/W2125391419","https://openalex.org/W2225156818","https://openalex.org/W2337532627","https://openalex.org/W2777186991","https://openalex.org/W2786712888","https://openalex.org/W2788755844","https://openalex.org/W2884645299","https://openalex.org/W2909445826","https://openalex.org/W2948364217","https://openalex.org/W2964059111","https://openalex.org/W2978575375","https://openalex.org/W3043426275","https://openalex.org/W3046992262","https://openalex.org/W3049691931","https://openalex.org/W3087507349","https://openalex.org/W3129756400","https://openalex.org/W3176923149","https://openalex.org/W3194838893","https://openalex.org/W3200929057","https://openalex.org/W3212073575","https://openalex.org/W4211210278","https://openalex.org/W4225510469","https://openalex.org/W4229801112","https://openalex.org/W4249256225","https://openalex.org/W4251795899","https://openalex.org/W6684488266","https://openalex.org/W6833688756"],"related_works":["https://openalex.org/W3082178636","https://openalex.org/W1521968289","https://openalex.org/W2782041652","https://openalex.org/W2952088488","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Deep":[0],"neural":[1,94],"networks":[2],"(DNNs)":[3],"have":[4],"already":[5],"impacted":[6],"the":[7,67,85,98,147,168,171,175,182,185,194,203,221],"field":[8],"of":[9,100,122,158,184],"medicine":[10],"in":[11,28,191,227],"data":[12,225],"analysis,":[13],"classification,":[14],"and":[15,45,52,113,129,150,170,187],"image":[16],"processing.":[17],"Unfortunately,":[18],"their":[19],"performance":[20],"is":[21],"drastically":[22],"reduced":[23],"when":[24],"datasets":[25],"are":[26],"scarce":[27],"nature":[29],"(e.g.,":[30],"rare":[31],"diseases":[32],"or":[33],"early-research":[34],"data).":[35],"In":[36,70],"such":[37],"scenarios,":[38],"DNNs":[39],"display":[40],"poor":[41],"capacity":[42],"for":[43,78,83,97,219],"generalization":[44],"often":[46],"lead":[47],"to":[48,65,146],"highly":[49],"biased":[50],"estimates":[51],"silent":[53],"failures.":[54],"Moreover,":[55],"deterministic":[56],"systems":[57],"cannot":[58],"provide":[59],"epistemic":[60],"uncertainty,":[61],"a":[62,75,81,91,120,211,216],"key":[63],"component":[64],"asserting":[66],"model's":[68,195],"reliability.":[69],"this":[71],"work,":[72],"we":[73,89],"developed":[74],"probabilistic":[76],"system":[77],"classification":[79,99,176,230],"as":[80],"framework":[82],"addressing":[84,220],"aforementioned":[86],"criticalities.":[87],"Specifically,":[88],"implemented":[90],"Bayesian":[92,136,172,212],"convolutional":[93],"network":[95],"(BCNN)":[96],"cardiac":[101],"amyloidosis":[102],"(CA)":[103],"subtypes.":[104],"We":[105,115],"prepared":[106],"four":[107],"different":[108],"CNNs:":[109],"base-deterministic,":[110,148],"dropout-deterministic,":[111,149],"dropout-Bayesian,":[112],"Bayesian.":[114],"then":[116],"trained":[117],"them":[118],"on":[119],"dataset":[121],"1107":[123],"PET":[124],"images":[125],"from":[126],"47":[127],"CA":[128],"control":[130],"patients":[131],"(data":[132],"scarcity":[133,226],"scenario).":[134],"The":[135,206],"model":[137],"achieved":[138],"performances":[139],"(78.28":[140],"(1.99)":[141],"%":[142],"test":[143],"accuracy)":[144],"comparable":[145],"dropout-Bayesian":[151,169],"ones,":[152],"while":[153,180],"showing":[154],"strongly":[155],"increased":[156,193],"\"Out":[157],"Distribution\"":[159],"input":[160],"detection":[161],"(validation-test":[162],"accuracy":[163],"mismatch":[164],"reduction).":[165],"Additionally,":[166],"both":[167],"models":[173],"enriched":[174],"through":[177],"confidence":[178],"estimates,":[179],"reducing":[181],"criticalities":[183],"dropout-deterministic":[186],"base-deterministic":[188],"approaches.":[189],"This":[190],"turn":[192],"reliability,":[196],"also":[197],"providing":[198],"much":[199],"needed":[200],"insights":[201],"into":[202],"network's":[204],"estimates.":[205],"obtained":[207],"results":[208],"suggest":[209],"that":[210],"CNN":[213],"can":[214],"be":[215],"promising":[217],"solution":[218],"challenges":[222],"posed":[223],"by":[224],"medical":[228],"imaging":[229],"tasks.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":4}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
