Please use this identifier to cite or link to this item: https://observatorio.fm.usp.br/handle/OPI/45807
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dc.contributorSistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP-
dc.contributor.authorBULTEN, Wouter-
dc.contributor.authorBALKENHOL, Maschenka-
dc.contributor.authorBELINGA, Jean-Joel Awoumou-
dc.contributor.authorBRILHANTE, Americo-
dc.contributor.authorCAKIR, Asli-
dc.contributor.authorEGEVAD, Lars-
dc.contributor.authorEKLUND, Martin-
dc.contributor.authorFARRE, Xavier-
dc.contributor.authorGERONATSIOU, Katerina-
dc.contributor.authorMOLINIE, Vincent-
dc.contributor.authorPEREIRA, Guilherme-
dc.contributor.authorROY, Paromita-
dc.contributor.authorSAILE, Gunter-
dc.contributor.authorSALLES, Paulo-
dc.contributor.authorSCHAAFSMA, Ewout-
dc.contributor.authorTSCHUI, Joelle-
dc.contributor.authorVOS, Anne-Marie-
dc.contributor.authorBOVEN, Hester van-
dc.contributor.authorVINK, Robert-
dc.contributor.authorLAAK, Jeroen van der-
dc.contributor.authorKAA, Christina Hulsbergen-van der-
dc.contributor.authorLITJENS, Geert-
dc.date.accessioned2022-04-19T12:54:43Z-
dc.date.available2022-04-19T12:54:43Z-
dc.date.issued2021-
dc.identifier.citationMODERN PATHOLOGY, v.34, n.3, p.660-671, 2021-
dc.identifier.issn0893-3952-
dc.identifier.urihttps://observatorio.fm.usp.br/handle/OPI/45807-
dc.description.abstractThe Gleason score is the most important prognostic marker for prostate cancer patients, but it suffers from significant observer variability. Artificial intelligence (AI) systems based on deep learning can achieve pathologist-level performance at Gleason grading. However, the performance of such systems can degrade in the presence of artifacts, foreign tissue, or other anomalies. Pathologists integrating their expertise with feedback from an AI system could result in a synergy that outperforms both the individual pathologist and the system. Despite the hype around AI assistance, existing literature on this topic within the pathology domain is limited. We investigated the value of AI assistance for grading prostate biopsies. A panel of 14 observers graded 160 biopsies with and without AI assistance. Using AI, the agreement of the panel with an expert reference standard increased significantly (quadratically weighted Cohen's kappa, 0.799 vs. 0.872;p = 0.019). On an external validation set of 87 cases, the panel showed a significant increase in agreement with a panel of international experts in prostate pathology (quadratically weighted Cohen's kappa, 0.733 vs. 0.786;p = 0.003). In both experiments, on a group-level, AI-assisted pathologists outperformed the unassisted pathologists and the standalone AI system. Our results show the potential of AI systems for Gleason grading, but more importantly, show the benefits of pathologist-AI synergy.eng
dc.description.sponsorshipDutch Cancer Society (KWF)KWF Kankerbestrijding [KUN 2015-7970]-
dc.language.isoeng-
dc.publisherSPRINGERNATUREeng
dc.relation.ispartofModern Pathology-
dc.rightsrestrictedAccesseng
dc.subject.otherinterobserver reproducibilityeng
dc.subject.othercarcinomaeng
dc.subject.othercancereng
dc.titleArtificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologistseng
dc.typearticleeng
dc.rights.holderCopyright SPRINGERNATUREeng
dc.contributor.groupauthorISUP Pathology Imagebase Expert Pa-
dc.contributor.groupauthorLEITE, Katia R. M.-
dc.identifier.doi10.1038/s41379-020-0640-y-
dc.identifier.pmid32759979-
dc.subject.wosPathologyeng
dc.type.categoryoriginal articleeng
dc.type.versionpublishedVersioneng
hcfmusp.author.externalBULTEN, Wouter:Radboud Univ Nijmegen, Radboud Inst Hlth Sci, Dept Pathol, Med Ctr, Nijmegen, Netherlands-
hcfmusp.author.externalBALKENHOL, Maschenka:Radboud Univ Nijmegen, Radboud Inst Hlth Sci, Dept Pathol, Med Ctr, Nijmegen, Netherlands-
hcfmusp.author.externalBELINGA, Jean-Joel Awoumou:Univ Yaounde I, Dept Morphol Sci & Anat Pathol, Fac Med & Biomed Sci, Yaounde, Cameroon-
hcfmusp.author.externalBRILHANTE, Americo:Salomao Zoppi Diagnost DASA, Sao Paulo, Brazil-
hcfmusp.author.externalCAKIR, Asli:Istanbul Medipol Univ, Sch Med, Pathol Dept, Istanbul, Turkey-
hcfmusp.author.externalEGEVAD, Lars:Karolinska Inst, Dept Oncol & Pathol, Stockholm, Sweden-
hcfmusp.author.externalEKLUND, Martin:Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden-
hcfmusp.author.externalFARRE, Xavier:Publ Hlth Agcy Catalonia, Dept Hlth, Lleida, Catalonia, Spain-
hcfmusp.author.externalGERONATSIOU, Katerina:Hop Diaconat Mulhouse, Ctr Pathol, Mulhouse, France-
hcfmusp.author.externalMOLINIE, Vincent:Aix en Provence Hosp, Pathol Dept, Aix En Provence, France-
hcfmusp.author.externalPEREIRA, Guilherme:Histo Patol Cirarg & Citol, Joao Pessoa, Paraiba, Brazil-
hcfmusp.author.externalROY, Paromita:Tata Med Ctr, Dept Pathol, Kolkata, India-
hcfmusp.author.externalSAILE, Gunter:Abt Histopathol & Zytol, Iabor Team W Ag, Goldach Sg, Switzerland-
hcfmusp.author.externalSALLES, Paulo:Inst Mario Penna, Belo Horizonte, MG, Brazil-
hcfmusp.author.externalSCHAAFSMA, Ewout:Radboud Univ Nijmegen, Radboud Inst Hlth Sci, Dept Pathol, Med Ctr, Nijmegen, Netherlands-
hcfmusp.author.externalTSCHUI, Joelle:Med Pathol, Bern, Switzerland-
hcfmusp.author.externalVOS, Anne-Marie:Radboud Univ Nijmegen, Radboud Inst Hlth Sci, Dept Pathol, Med Ctr, Nijmegen, Netherlands-
hcfmusp.author.externalBOVEN, Hester van:Antoni van Leeuwenhoek Hosp, Netherlands Canc Inst, Dept Pathol, Amsterdam, Netherlands-
hcfmusp.author.externalVINK, Robert:Lab Pathol East Netherlands, Hengelo, Netherlands-
hcfmusp.author.externalLAAK, Jeroen van der:Radboud Univ Nijmegen, Radboud Inst Hlth Sci, Dept Pathol, Med Ctr, Nijmegen, Netherlands; Linkoping Univ, Ctr Med Image Sci & Visualizat, Linkoping, Sweden-
hcfmusp.author.externalKAA, Christina Hulsbergen-van der:Lab Pathol East Netherlands, Hengelo, Netherlands-
hcfmusp.author.externalLITJENS, Geert:Radboud Univ Nijmegen, Radboud Inst Hlth Sci, Dept Pathol, Med Ctr, Nijmegen, Netherlands-
hcfmusp.description.beginpage660-
hcfmusp.description.endpage671-
hcfmusp.description.issue3-
hcfmusp.description.volume34-
hcfmusp.origemWOS-
hcfmusp.origem.idWOS:000556178900003-
hcfmusp.origem.id2-s2.0-85089025736-
hcfmusp.publisher.cityLONDONeng
hcfmusp.publisher.countryENGLANDeng
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dc.description.indexMEDLINEeng
dc.identifier.eissn1530-0285-
hcfmusp.citation.scopus20-
hcfmusp.scopus.lastupdate2022-08-11-
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