Tilman T. Rau, William Cross, Ricardo R. Lastra, Regina C‐L. Lo, Andres Matoso and C. Simon Herrington 2024. Closing the loop – the role of pathologists in digital and computational pathology research. The Journal of Pathology: Clinical Research. 10 (2) e12366. https://doi.org/10.1002/2056-4538.12366
| Title | Closing the loop – the role of pathologists in digital and computational pathology research |
|---|---|
| Type | Edited issue |
| Authors | Tilman T. Rau, William Cross, Ricardo R. Lastra, Regina C‐L. Lo, Andres Matoso and C. Simon Herrington |
| Abstract | An increasing number of manuscripts related to digital and computational pathology are being submitted to The Journal of Pathology: Clinical Research as part of the continuous evolution from digital imaging and algorithm-based digital pathology to computational pathology and artificial intelligence. However, despite these technological advances, tissue analysis still relies heavily on pathologists' annotations. There are three crucial elements to the pathologist's role during annotation tasks: granularity, time constraints, and responsibility for the interpretation of computational results. Granularity involves detailed annotations, including case level, regional, and cellular features; and integration of attributions from different sources. Time constraints due to pathologist shortages have led to the development of techniques to expedite annotation tasks from cell-level attributions up to so-called unsupervised learning. The impact of pathologists may seem diminished, but their role is crucial in providing ground truth and connecting pathological knowledge generation with computational advancements. Measures to display results back to pathologists and reflections about correctly applied diagnostic criteria are mandatory to maintain fidelity during human–machine interactions. Collaboration and iterative processes, such as human-in-the-loop machine learning are key for continuous improvement, ensuring the pathologist's involvement in evaluating computational results and closing the loop for clinical applicability. The journal is interested particularly in the clinical diagnostic application of computational pathology and invites submissions that address the issues raised in this editorial. |
| Article number | e12366 |
| Journal | The Journal of Pathology: Clinical Research |
| Journal citation | 10 (2) |
| ISSN | 2056-4538 |
| Year | 2024 |
| Publisher | Wiley |
| Publisher's version | License CC BY 4.0 File Access Level Open (open metadata and files) |
| Digital Object Identifier (DOI) | https://doi.org/10.1002/2056-4538.12366 |
| Web address (URL) | https://doi.org/10.1002/2056-4538.12366 |
| Publication dates | |
| Published | 10 Mar 2024 |