{"id":"https://openalex.org/W4286816990","doi":"https://doi.org/10.1186/s12859-022-04845-1","title":"Exploiting generative self-supervised learning for the assessment of biological images with lack of annotations","display_name":"Exploiting generative self-supervised learning for the assessment of biological images with lack of annotations","publication_year":2022,"publication_date":"2022-07-24","ids":{"openalex":"https://openalex.org/W4286816990","doi":"https://doi.org/10.1186/s12859-022-04845-1","pmid":"https://pubmed.ncbi.nlm.nih.gov/35871688"},"language":"en","primary_location":{"id":"doi:10.1186/s12859-022-04845-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-04845-1","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-04845-1","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","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":"BMC Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-04845-1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006895284","display_name":"Alessio Mascolini","orcid":"https://orcid.org/0000-0003-4213-7729"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Alessio Mascolini","raw_affiliation_strings":["Polytechnic University of Turin, Corso Duca Degli Abruzzi, Turin, Italy. alessio.mascolini@polito.it","Polytechnic University of Turin, Corso Duca Degli Abruzzi, Turin, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Polytechnic University of Turin, Corso Duca Degli Abruzzi, Turin, Italy. alessio.mascolini@polito.it","institution_ids":["https://openalex.org/I177477856"]},{"raw_affiliation_string":"Polytechnic University of Turin, Corso Duca Degli Abruzzi, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090505273","display_name":"Dario Cardamone","orcid":"https://orcid.org/0000-0002-4006-5277"},"institutions":[{"id":"https://openalex.org/I4210121412","display_name":"Toscana Life Sciences","ror":"https://ror.org/01xze8742","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210121412"]},{"id":"https://openalex.org/I55143463","display_name":"University of Turin","ror":"https://ror.org/048tbm396","country_code":"IT","type":"education","lineage":["https://openalex.org/I55143463"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Dario Cardamone","raw_affiliation_strings":["Toscana Life Sciences Foundation, Siena, Italy","University of Turin, Via Giuseppe Verdi, Turin, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toscana Life Sciences Foundation, Siena, Italy","institution_ids":["https://openalex.org/I4210121412"]},{"raw_affiliation_string":"University of Turin, Via Giuseppe Verdi, Turin, Italy","institution_ids":["https://openalex.org/I55143463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031161800","display_name":"Francesco Ponzio","orcid":"https://orcid.org/0000-0002-8472-8247"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Ponzio","raw_affiliation_strings":["Polytechnic University of Turin, Corso Duca Degli Abruzzi, Turin, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Polytechnic University of Turin, Corso Duca Degli Abruzzi, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028610334","display_name":"Santa Di Cataldo","orcid":"https://orcid.org/0000-0002-6239-8945"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Santa Di Cataldo","raw_affiliation_strings":["Polytechnic University of Turin, Corso Duca Degli Abruzzi, Turin, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Polytechnic University of Turin, Corso Duca Degli Abruzzi, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068452817","display_name":"Elisa Ficarra","orcid":"https://orcid.org/0000-0002-8061-2124"},"institutions":[{"id":"https://openalex.org/I122346577","display_name":"University of Modena and Reggio Emilia","ror":"https://ror.org/02d4c4y02","country_code":"IT","type":"education","lineage":["https://openalex.org/I122346577"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Elisa Ficarra","raw_affiliation_strings":["University of Modena e Reggio Emilia, Via Universit\u00e0, Modena, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Modena e Reggio Emilia, Via Universit\u00e0, Modena, Italy","institution_ids":["https://openalex.org/I122346577"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5006895284"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":{"value":2790,"currency":"USD","value_usd":2790},"apc_paid":{"value":2245,"currency":"EUR","value_usd":2421},"fwci":3.9468,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.93366787,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"23","issue":"1","first_page":"295","last_page":"295"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.698199987411499,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.698199987411499,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.05869999900460243,"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/T10862","display_name":"AI in cancer detection","score":0.04179999977350235,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.8462493419647217},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7801640033721924},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7193485498428345},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6199607849121094},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5944963097572327},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.549934983253479},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5426779389381409},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5320675373077393},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5201876163482666},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4662190079689026},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.459835946559906},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4512736201286316},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.4370110332965851},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4340648651123047},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3244427442550659}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.8462493419647217},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7801640033721924},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7193485498428345},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6199607849121094},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5944963097572327},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.549934983253479},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5426779389381409},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5320675373077393},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5201876163482666},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4662190079689026},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.459835946559906},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4512736201286316},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.4370110332965851},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4340648651123047},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3244427442550659},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002452","descriptor_name":"Cell Count","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002452","descriptor_name":"Cell Count","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002452","descriptor_name":"Cell Count","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002522","descriptor_name":"Chlorocebus aethiops","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002522","descriptor_name":"Chlorocebus aethiops","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002522","descriptor_name":"Chlorocebus aethiops","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":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":6,"locations":[{"id":"doi:10.1186/s12859-022-04845-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-04845-1","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-04845-1","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","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":"BMC Bioinformatics","raw_type":"journal-article"},{"id":"pmid:35871688","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35871688","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":"BMC bioinformatics","raw_type":null},{"id":"pmh:oai:arXiv.org:2107.07761","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.07761","pdf_url":"https://arxiv.org/pdf/2107.07761","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9308954","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9308954","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":"BMC Bioinformatics","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:65fa4f7733274709b0e7373d9d136e34","is_oa":true,"landing_page_url":"https://doaj.org/article/65fa4f7733274709b0e7373d9d136e34","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics, Vol 23, Iss 1, Pp 1-17 (2022)","raw_type":"article"},{"id":"pmh:oai:iris.unimore.it:11380/1284304","is_oa":true,"landing_page_url":"http://hdl.handle.net/11380/1284304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400718","display_name":"IRIS UNIMORE (University of Modena and Reggio Emilia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I122346577","host_organization_name":"University of Modena and Reggio Emilia","host_organization_lineage":["https://openalex.org/I122346577"],"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":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1186/s12859-022-04845-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-04845-1","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-04845-1","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","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":"BMC Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G434337789","display_name":null,"funder_award_id":"HORIZON2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8000286611","display_name":"Improved clinical decisions via integrating multiple data levels to overcome chemotherapy resistance in high-grade serous ovarian cancer","funder_award_id":"965193","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4286816990.pdf","grobid_xml":"https://content.openalex.org/works/W4286816990.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2762941833","https://openalex.org/W2775908481","https://openalex.org/W2790824977","https://openalex.org/W2804905867","https://openalex.org/W2900116731","https://openalex.org/W2917997586","https://openalex.org/W2969985801","https://openalex.org/W2984353870","https://openalex.org/W3019802146","https://openalex.org/W3023371261","https://openalex.org/W3027451324","https://openalex.org/W3035574324","https://openalex.org/W3035725276","https://openalex.org/W3041133507","https://openalex.org/W3047640609","https://openalex.org/W3092609815","https://openalex.org/W3093261564","https://openalex.org/W3093385833","https://openalex.org/W3094575259","https://openalex.org/W3108516814","https://openalex.org/W3162059838","https://openalex.org/W3196174677","https://openalex.org/W3204014573","https://openalex.org/W4229067108","https://openalex.org/W4285121879","https://openalex.org/W4287905206","https://openalex.org/W4294643153","https://openalex.org/W6600018615","https://openalex.org/W6600281908","https://openalex.org/W6818723395"],"related_works":["https://openalex.org/W3217069185","https://openalex.org/W3049340819","https://openalex.org/W4308928038","https://openalex.org/W4200430540","https://openalex.org/W3141413246","https://openalex.org/W2808862658","https://openalex.org/W4322709305","https://openalex.org/W3002487853","https://openalex.org/W3010213975","https://openalex.org/W2964074194"],"abstract_inverted_index":{"MOTIVATION:":[0],"Computer-aided":[1],"analysis":[2],"of":[3,53,86],"biological":[4,55],"images":[5],"typically":[6],"requires":[7],"extensive":[8],"training":[9],"on":[10,38,70],"large-scale":[11],"annotated":[12],"datasets,":[13],"which":[14,42],"is":[15,169],"not":[16,121,136],"viable":[17],"in":[18,50,89,140],"many":[19],"situations.":[20],"In":[21,111],"this":[22,75],"paper,":[23],"we":[24,43],"present":[25],"Generative":[26,62],"Adversarial":[27,63],"Network":[28],"Discriminator":[29],"Learner":[30],"(GAN-DL),":[31],"a":[32,141,150],"novel":[33],"self-supervised":[34,46,142],"learning":[35,49],"paradigm":[36],"based":[37,69],"the":[39,51,84,94,103,154],"StyleGAN2":[40,168],"architecture,":[41],"employ":[44],"for":[45,83,153],"image":[47],"representation":[48],"case":[52],"fluorescent":[54],"images.":[56,72],"RESULTS:":[57],"We":[58,73],"show":[59],"that":[60],"Wasserstein":[61],"Networks":[64],"enable":[65],"high-throughput":[66],"compound":[67],"screening":[68],"raw":[71],"demonstrate":[74],"by":[76],"classifying":[77],"active":[78],"and":[79,102,125,162],"inactive":[80],"compounds":[81],"tested":[82,155],"inhibition":[85],"SARS-CoV-2":[87],"infection":[88],"two":[90],"different":[91],"cell":[92],"models:":[93],"primary":[95],"human":[96],"renal":[97],"cortical":[98],"epithelial":[99,108],"cells":[100,109],"(HRCE)":[101],"African":[104],"green":[105],"monkey":[106],"kidney":[107],"(VERO).":[110],"contrast":[112],"to":[113,130],"previous":[114],"methods,":[115],"our":[116],"deep":[117],"learning-based":[118],"approach":[119],"does":[120],"require":[122],"any":[123],"annotation,":[124],"can":[126,147],"also":[127],"be":[128],"used":[129],"solve":[131],"subtle":[132],"tasks":[133],"it":[134,146],"was":[135],"specifically":[137],"trained":[138],"on,":[139],"manner.":[143],"For":[144],"example,":[145],"effectively":[148],"derive":[149],"dose-response":[151],"curve":[152],"treatments.":[156],"AVAILABILITY":[157],"AND":[158],"IMPLEMENTATION:":[159],"Our":[160],"code":[161],"embeddings":[163],"are":[164],"available":[165,170],"at":[166,171],"https://gitlab.com/AlesioRFM/gan-dl":[167],"https://github.com/NVlabs/stylegan2":[172],".":[173]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}