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Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps

Pinckaers Hans; Wählby Carolina; Mulliqi Nita; Lindberg Johan; Egevad Lars; Litjens Geert; Ji Xiaoyi; Eklund Martin; Ruusuvuori Pekka; Olsson Henrik; Tsuzuki Toyonori; Kartasalo Kimmo; Chen Po-Hsuan Cameron; Bulten Wouter; Samaratunga Hemamali; Rantalainen Mattias; Delahunt Brett

dc.contributor.authorPinckaers Hans
dc.contributor.authorWählby Carolina
dc.contributor.authorMulliqi Nita
dc.contributor.authorLindberg Johan
dc.contributor.authorEgevad Lars
dc.contributor.authorLitjens Geert
dc.contributor.authorJi Xiaoyi
dc.contributor.authorEklund Martin
dc.contributor.authorRuusuvuori Pekka
dc.contributor.authorOlsson Henrik
dc.contributor.authorTsuzuki Toyonori
dc.contributor.authorKartasalo Kimmo
dc.contributor.authorChen Po-Hsuan Cameron
dc.contributor.authorBulten Wouter
dc.contributor.authorSamaratunga Hemamali
dc.contributor.authorRantalainen Mattias
dc.contributor.authorDelahunt Brett
dc.date.accessioned2022-10-28T14:42:59Z
dc.date.available2022-10-28T14:42:59Z
dc.identifier.urihttps://www.utupub.fi/handle/10024/172944
dc.description.abstract<p>Diagnosis and Gleason grading of prostate cancer in biopsies are critical for the clinical management of men with prostate cancer. Despite this, the high grading variability among pathologists leads to the potential for under- and overtreatment. Artificial intelligence (AI) systems have shown promise in assisting pathologists to perform Gleason grading, which could help address this problem. In this mini-review, we highlight studies reporting on the development of AI systems for cancer detection and Gleason grading, and discuss the progress needed for widespread clinical implementation, as well as anticipated future developments.</p><p>Patient summary<br>This mini-review summarizes the evidence relating to the validation of artificial intelligence (AI)-assisted cancer detection and Gleason grading of prostate cancer in biopsies, and highlights the remaining steps required prior to its widespread clinical implementation. We found that, although there is strong evidence to show that AI is able to perform Gleason grading on par with experienced uropathologists, more work is needed to ensure the accuracy of results from AI systems in diverse settings across different patient populations, digitization platforms, and pathology laboratories.</p>
dc.language.isoen
dc.titleArtificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps
dc.identifier.urnURN:NBN:fi-fe2021102752717
dc.relation.volume7
dc.contributor.organizationfi=tyks, vsshp|en=tyks, vsshp|
dc.contributor.organizationfi=biolääketieteen laitos, yhteiset|en=Institute of Biomedicine|
dc.contributor.organization-code2607100
dc.converis.publication-id66879438
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/66879438
dc.format.pagerange691
dc.format.pagerange687
dc.identifier.eissn2405-4569
dc.identifier.jour-issn2405-4569
dc.okm.affiliatedauthorRuusuvuori, Pekka
dc.okm.affiliatedauthorDataimport, tyks, vsshp
dc.okm.discipline3122 Syöpätauditfi_FI
dc.okm.discipline3122 Cancersen_GB
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA2 Review article
dc.publisher.countryNetherlandsen_GB
dc.publisher.countryAlankomaatfi_FI
dc.publisher.country-codeNL
dc.relation.doi10.1016/j.euf.2021.07.002
dc.relation.ispartofjournalEuropean Urology Focus
dc.relation.issue4
dc.year.issued2021


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