Automated quality assessment of large digitised histology cohorts by artificial intelligence

Research using whole slide images (WSIs) of histopathology slides has increased exponentially over recent years. Glass slides from retrospective cohorts, some with patient follow-up data are digitised for the development and validation of artificial intelligence (AI) tools. Such resources, therefore...

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Vydáno v:	Scientific reports Ročník 12; číslo 1; s. 5002 - 16
Hlavní autoři:	Haghighat, Maryam, Browning, Lisa, Sirinukunwattana, Korsuk, Malacrino, Stefano, Khalid Alham, Nasullah, Colling, Richard, Cui, Ying, Rakha, Emad, Hamdy, Freddie C., Verrill, Clare, Rittscher, Jens
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Nature Publishing Group UK 23.03.2022 Nature Publishing Group Nature Portfolio
Témata:	631/114/1564 692/699/67/2321 Algorithms Artificial Intelligence Automation Colorectal cancer Colorectal carcinoma Histology Histopathology Humanities and Social Sciences Humans Image Interpretation, Computer-Assisted - methods Machine learning Male multidisciplinary Neural networks Neural Networks, Computer Prostate Prostate cancer Quality control Retrospective Studies Science Science (multidisciplinary) Usability
ISSN:	2045-2322, 2045-2322
On-line přístup:	Získat plný text
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