Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Milda Pocevičiūtė"'
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-15 (2022)
Abstract Deep learning (DL) has shown great potential in digital pathology applications. The robustness of a diagnostic DL-based solution is essential for safe clinical deployment. In this work we evaluate if adding uncertainty estimates for DL predi
Externí odkaz:
https://doaj.org/article/136a8712cbfe449da4d5cdce3b0eeacb
Autor:
Sofia Jarkman, Micael Karlberg, Milda Pocevičiūtė, Anna Bodén, Péter Bándi, Geert Litjens, Claes Lundström, Darren Treanor, Jeroen van der Laak
Publikováno v:
Cancers; Volume 14; Issue 21; Pages: 5424
Cancers, 14
Cancers, 14, 21
Cancers, 14
Cancers, 14, 21
Simple Summary Pathology is a cornerstone in cancer diagnostics, and digital pathology and artificial intelligence-driven image analysis could potentially save time and enhance diagnostic accuracy. For clinical implementation of artificial intelligen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65526186a0775a9a3a0677725d6b6b09
Publikováno v:
Artificial Intelligence and Machine Learning for Digital Pathology ISBN: 9783030504014
AI and ML for Digital Pathology
AI and ML for Digital Pathology
Artificial intelligence (AI) has shown great promise for diagnostic imaging assessments. However, the application of AI to support medical diagnostics in clinical routine comes with many challenges. The algorithms should have high prediction accuracy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c38010f97a34aa7ad89e9c68aedc164
https://doi.org/10.1007/978-3-030-50402-1_4
https://doi.org/10.1007/978-3-030-50402-1_4
