Artificial intelligence for diagnosis and Gleason grading of prostate cancer: The PANDA challenge

Basit Öğe Kaydı
dc.authorid0000-0003-0128-6947
dc.contributor.authorBulten, Wouter
dc.contributor.authorKartasalo, Kimmo
dc.contributor.authorChen, Po-Hsuan Cameron
dc.contributor.authorStröm, Peter
dc.contributor.authorPinckaers, Hans
dc.contributor.authorNagpal, Kunal
dc.contributor.authorCai, Yuannan
dc.contributor.authorSteiner, David F.
dc.contributor.authorvan Boven, Hester
dc.contributor.authorVink, Robert
dc.contributor.authorHulsbergen-van de Kaa, Christina
dc.contributor.authorvan der Laak, Jeroen
dc.contributor.authorAmin, Mahul B.
dc.contributor.authorEvans, Andrew J.
dc.contributor.authorvan der Kwast, Theodorus
dc.contributor.authorAllan, Robert
dc.contributor.authorHumphrey, Peter A.
dc.contributor.authorGrönberg, Henrik
dc.contributor.authorSamaratunga, Hemamali
dc.contributor.authorDelahunt, Brett
dc.contributor.authorTsuzuki, Toyonori
dc.contributor.authorHäkkinen, Tomi
dc.contributor.authorEgevad, Lars
dc.contributor.authorDemkin, Maggie
dc.contributor.authorDane, Sohier
dc.contributor.authorTan, Fraser
dc.contributor.authorValkonen, Masi
dc.contributor.authorCorrado, Greg S.
dc.contributor.authorPeng, Lily
dc.contributor.authorMermel, Craig H.
dc.contributor.authorRuusuvuori, Pekka
dc.contributor.authorLitjens, Geert
dc.contributor.authorEklund, Martin
dc.contributor.authorBrilhante, Américo
dc.contributor.authorÇakır, Aslı
dc.contributor.authorFarré, Xavier
dc.contributor.authorGeronatsiou, Katerina
dc.contributor.authorMolinié, Vincent
dc.contributor.authorPereira, Guilherme
dc.contributor.authorRoy, Paromita
dc.contributor.authorSaile, Günter
dc.contributor.authorSalles, Paulo G. O.
dc.contributor.authorSchaafsma, Ewout
dc.contributor.authorTschui, Joëlle
dc.contributor.authorBilloch-Lima, Jorge
dc.contributor.authorPereira, Emíio M.
dc.contributor.authorZhou, Ming
dc.contributor.authorHe, Shujun
dc.contributor.authorSong, Sejun
dc.contributor.authorSun, Qing
dc.contributor.authorYoshihara, Hiroshi
dc.contributor.authorYamaguchi, Taiki
dc.contributor.authorOno, Kosaku
dc.contributor.authorShen, Tao
dc.contributor.authorJi, Jianyi
dc.contributor.authorRoussel, Arnaud
dc.contributor.authorZhou, Kairong
dc.contributor.authorChai, Tianrui
dc.contributor.authorWeng, Nina
dc.contributor.authorGrechka, Dmitry
dc.date.accessioned2022-12-19T10:48:43Z
dc.date.available2022-12-19T10:48:43Z
dc.date.issued2022
dc.departmentİstanbul Medipol Üniversitesi, Tıp Fakültesi, Cerrahi Tıp Bilimleri Bölümü, Tıbbi Patoloji Ana Bilim Dalı
dc.description.abstractThrough a community-driven competition, the PANDA challenge provides a curated diverse dataset and a catalog of models for prostate cancer pathology, and represents a blueprint for evaluating AI algorithms in digital pathology. Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies. However, results have been limited to individual studies, lacking validation in multinational settings. Competitions have been shown to be accelerators for medical imaging innovations, but their impact is hindered by lack of reproducibility and independent validation. With this in mind, we organized the PANDA challenge-the largest histopathology competition to date, joined by 1,290 developers-to catalyze development of reproducible AI algorithms for Gleason grading using 10,616 digitized prostate biopsies. We validated that a diverse set of submitted algorithms reached pathologist-level performance on independent cross-continental cohorts, fully blinded to the algorithm developers. On United States and European external validation sets, the algorithms achieved agreements of 0.862 (quadratically weighted kappa, 95% confidence interval (CI), 0.840-0.884) and 0.868 (95% CI, 0.835-0.900) with expert uropathologists. Successful generalization across different patient populations, laboratories and reference standards, achieved by a variety of algorithmic approaches, warrants evaluating AI-based Gleason grading in prospective clinical trials.
dc.description.sponsorshipKWF Kankerbestrijding ; Netherlands Organization for Scientific Research (NWO) ; Swedish Research Council European Commission ; Swedish Cancer Society ; Swedish eScience Research Center ; Ake Wiberg Foundation ; Prostatacancerforbundet ; Academy of Finland ; Cancer Foundation Finland ; Google Incorporated ; MICCAI board challenge working group ; Verily Life Sciences ; EIT Health ; Karolinska Institutet ; MICCAI 2020 satellite event team ; ERAPerMeden_US
dc.identifier.citationBulten, W., Kartasalo, K., Chen, Po-H. C., Ström, P., Pinckaers, H., Nagpal, K. ... Grechka, D. (2022). Artificial intelligence for diagnosis and Gleason grading of prostate cancer: The PANDA challenge. Nature Medicine, 28(1), 154-+. https://doi.org/10.1038/s41591-021-01620-2
dc.identifier.doi10.1038/s41591-021-01620-2
dc.identifier.endpage+
dc.identifier.issn1078-8956
dc.identifier.issn1546-170X
dc.identifier.issue1
dc.identifier.pmid35027755
dc.identifier.scopus2-s2.0-85122887634
dc.identifier.scopusqualityQ1
dc.identifier.startpage154
dc.identifier.urihttps://doi.org/10.1038/s41591-021-01620-2
dc.identifier.urihttps://hdl.handle.net/20.500.12511/10146
dc.identifier.volume28
dc.identifier.wos000742323900003en_US
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorÇakır, Aslı
dc.language.isoen
dc.publisherNature Research
dc.relation.ispartofNature Medicineen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsAttribution 4.0 International*
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectPANDA challenge
dc.subjectProstate Cancer
dc.subjectGleason Grading
dc.subjectArtificial Intelligence
dc.titleArtificial intelligence for diagnosis and Gleason grading of prostate cancer: The PANDA challenge
dc.typeArticle

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
Cakir-Asli-2022.pdf
Boyut:
6.99 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

Makale Koleksiyonu
PubMed İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu