Weakly supervised annotation-free cancer detection and prediction of genotype in routine histopathology

Autor:	Peter Leonard Schrammen, Amelie Echle, Philip Quirke, Lara R. Heij, Nicholas P. West, Jakob Nikolas Kather, Christian Trautwein, Jenny Chang-Claude, Narmin Ghaffari Laleh, Alexander Brobeil, Daniel Truhn, Heike I. Grabsch, Volkmar Schulz, Titus J. Brinker, Matthias Kloor, Elizabeth Alwers, Hermann Brenner, Michael Hoffmeister, Dirk Jäger
Přispěvatelé:	MUMC+: DA Pat AIOS (9), RS: GROW - R2 - Basic and Translational Cancer Biology, Pathologie, Publica
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	Adult Male Genotype Colorectal cancer Computer science MICROSATELLITE INSTABILITY colorectal cancer Computational biology Pathology and Forensic Medicine COLORECTAL-CANCER Cohort Studies Neoplastic Syndromes Hereditary medicine Humans Aged Aged 80 and over Receiver operating characteristic Artificial neural network business.industry Brain Neoplasms Deep learning Digital pathology Microsatellite instability Reproducibility of Results deep learning Middle Aged medicine.disease artificial intelligence Lynch syndrome Confidence interval Mutation Female Artificial intelligence business Colorectal Neoplasms digital pathology computational pathology
Zdroj:	Journal of Pathology, 256(1), 50-60. Wiley The journal of pathology 256(1), 50-60 (2022). doi:10.1002/path.5800
ISSN:	0022-3417
DOI:	10.1002/path.5800
Popis:	The journal of pathology 256(1), 50-60 (2022). doi:10.1002/path.5800 Published by Wiley, Bognor Regis [u.a.]
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9f204126dab46f39b95b92a10cb62df https://cris.maastrichtuniversity.nl/en/publications/e8d31f49-73c6-4c20-b1b9-2f07f7400f29 Zobrazit plný text záznamu Plný text