Zobrazeno 1 - 10
of 156
pro vyhledávání: '"Jens, Rittscher"'
Autor:
Maxime W. Lafarge, Enric Domingo, Korsuk Sirinukunwattana, Ruby Wood, Leslie Samuel, Graeme Murray, Susan D. Richman, Andrew Blake, David Sebag-Montefiore, Simon Gollins, Eckhard Klieser, Daniel Neureiter, Florian Huemer, Richard Greil, Philip Dunne, Philip Quirke, Lukas Weiss, Jens Rittscher, Tim Maughan, Viktor H. Koelzer
Publikováno v:
npj Precision Oncology, Vol 8, Iss 1, Pp 1-11 (2024)
Abstract The development of deep learning (DL) models to predict the consensus molecular subtypes (CMS) from histopathology images (imCMS) is a promising and cost-effective strategy to support patient stratification. Here, we investigate whether imCM
Externí odkaz:
https://doaj.org/article/069ba3e2373e479787af9c5a62731f11
Autor:
Hosuk Ryou, Korsuk Sirinukunwattana, Ruby Wood, Alan Aberdeen, Jens Rittscher, Olga K. Weinberg, Robert Hasserjian, Olga Pozdnyakova, Frank Peale, Brian Higgins, Pontus Lundberg, Kerstin Trunzer, Claire N. Harrison, Daniel Royston
Publikováno v:
HemaSphere, Vol 8, Iss 6, Pp n/a-n/a (2024)
Externí odkaz:
https://doaj.org/article/c15b24c8aece47aaad2f8fafe3b7bc77
Autor:
Sharib Ali, Noha Ghatwary, Debesh Jha, Ece Isik-Polat, Gorkem Polat, Chen Yang, Wuyang Li, Adrian Galdran, Miguel-Ángel González Ballester, Vajira Thambawita, Steven Hicks, Sahadev Poudel, Sang-Woong Lee, Ziyi Jin, Tianyuan Gan, ChengHui Yu, JiangPeng Yan, Doyeob Yeo, Hyunseok Lee, Nikhil Kumar Tomar, Mahmood Haithami, Amr Ahmed, Michael A. Riegler, Christian Daul, Pål Halvorsen, Jens Rittscher, Osama E. Salem, Dominique Lamarque, Renato Cannizzaro, Stefano Realdon, Thomas de Lange, James E. East
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal of polyps are highly op
Externí odkaz:
https://doaj.org/article/3d626e6de5c5444f94dfea2e49ff5ee3
Autor:
Ka Ho Tam, Maria F. Soares, Jesper Kers, Edward J. Sharples, Rutger J. Ploeg, Maria Kaisar, Jens Rittscher
Publikováno v:
Frontiers in Transplantation, Vol 3 (2024)
Two common obstacles limiting the performance of data-driven algorithms in digital histopathology classification tasks are the lack of expert annotations and the narrow diversity of datasets. Multi-instance learning (MIL) can address the former chall
Externí odkaz:
https://doaj.org/article/74e5aa5558d74e47a75f886017bc349d
Autor:
Lisa Browning, Christine Jesus, Stefano Malacrino, Yue Guan, Kieron White, Alison Puddle, Nasullah Khalid Alham, Maryam Haghighat, Richard Colling, Jacqueline Birks, Jens Rittscher, Clare Verrill
Publikováno v:
Diagnostics, Vol 14, Iss 10, p 990 (2024)
Digital pathology continues to gain momentum, with the promise of artificial intelligence to aid diagnosis and for assessment of features which may impact prognosis and clinical management. Successful adoption of these technologies depends upon the q
Externí odkaz:
https://doaj.org/article/f3a242266f4c4f8ebdb647d8f80e2409
Autor:
Sharib Ali, Debesh Jha, Noha Ghatwary, Stefano Realdon, Renato Cannizzaro, Osama E. Salem, Dominique Lamarque, Christian Daul, Michael A. Riegler, Kim V. Anonsen, Andreas Petlund, Pål Halvorsen, Jens Rittscher, Thomas de Lange, James E. East
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-17 (2023)
Abstract Polyps in the colon are widely known cancer precursors identified by colonoscopy. Whilst most polyps are benign, the polyp’s number, size and surface structure are linked to the risk of colon cancer. Several methods have been developed to
Externí odkaz:
https://doaj.org/article/6ce6480cdb454733b99a5a78de2cbf9e
Autor:
Maryam Haghighat, Lisa Browning, Korsuk Sirinukunwattana, Stefano Malacrino, Nasullah Khalid Alham, Richard Colling, Ying Cui, Emad Rakha, Freddie C. Hamdy, Clare Verrill, Jens Rittscher
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-16 (2022)
Abstract 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 ar
Externí odkaz:
https://doaj.org/article/1bfc88284dde4125a632fec35e0ca733
Publikováno v:
Biological Imaging, Vol 3 (2023)
The cell cycle is a complex biological phenomenon, which plays an important role in many cell biological processes and disease states. Machine learning is emerging to be a pivotal technique for the study of the cell cycle, resulting in a number of av
Externí odkaz:
https://doaj.org/article/590a03199aa04bde80c9aed92e6ee4dc
Autor:
Peipei Lu, Joseph Foley, Chunfang Zhu, Katherine McNamara, Korsuk Sirinukunwattana, Sujay Vennam, Sushama Varma, Hamid Fehri, Arunima Srivastava, Shirley Zhu, Jens Rittscher, Parag Mallick, Christina Curtis, Robert West
Publikováno v:
Breast Cancer Research, Vol 23, Iss 1, Pp 1-15 (2021)
Abstract Background The acquisition of oncogenic drivers is a critical feature of cancer progression. For some carcinomas, it is clear that certain genetic drivers occur early in neoplasia and others late. Why these drivers are selected and how these
Externí odkaz:
https://doaj.org/article/5a4a0026406d47478c68357b08b07dc8