1 code implementation • 23 Nov 2023 • Jack Breen, Katie Allen, Kieran Zucker, Nicolas M. Orsi, Nishant Ravikumar
Artificial intelligence has found increasing use for ovarian cancer morphological subtyping from histopathology slides, but the optimal magnification for computational interpretation is unclear.
1 code implementation • 19 Oct 2023 • Jack Breen, Katie Allen, Kieran Zucker, Geoff Hall, Nishant Ravikumar, Nicolas M. Orsi
For some therapies, it is not possible to predict patients' responses, potentially exposing them to the adverse effects of treatment without any therapeutic benefit.
no code implementations • 5 Aug 2023 • Jack Breen, Kieran Zucker, Katie Allen, Nishant Ravikumar, Nicolas M. Orsi
The rapid growth of digital pathology in recent years has provided an ideal opportunity for the development of artificial intelligence-based tools to improve the accuracy and efficiency of clinical diagnoses.
1 code implementation • 31 Mar 2023 • Jack Breen, Katie Allen, Kieran Zucker, Pratik Adusumilli, Andy Scarsbrook, Geoff Hall, Nicolas M. Orsi, Nishant Ravikumar
The inclusion criteria required that research evaluated AI on histopathology images for diagnostic or prognostic inferences in ovarian cancer.
1 code implementation • 17 Feb 2023 • Jack Breen, Katie Allen, Kieran Zucker, Geoff Hall, Nicolas M. Orsi, Nishant Ravikumar
Weakly-supervised classification of histopathology slides is a computationally intensive task, with a typical whole slide image (WSI) containing billions of pixels to process.