AI in Histopathology Explorer for comprehensive analysis of the evolving AI landscape in histopathology.
review · Level V
Where this comes from
- Record sourced from PubMed, PMID 40074858.
- Also identified by DOI 10.1038/s41746-025-01524-2 and PMC identifier 11904230.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Digital pathology and artificial intelligence (AI) hold immense transformative potential to revolutionize cancer diagnostics, treatment outcomes, and biomarker discovery. Gaining a deeper understanding of deep learning algorithm methods applied to histopathological data and evaluating their performance on different tasks is crucial for developing the next generation of AI technologies. To this end, we developed AI in Histopathology Explorer (HistoPathExplorer); an interactive dashboard with intelligent tools available at www.histopathexpo.ai . This real-time online resource enables users, including researchers, decision-makers, and various stakeholders, to assess the current landscape of AI applications for specific clinical tasks, analyze their performance, and explore the factors influencing their translation into practice. Moreover, a quality index was defined for evaluating the comprehensiveness of methodological details in published AI methods. HistoPathExplorer highlights opportunities and challenges for AI in histopathology, and offers a valuable resource for creating more effective methods and shaping strategies and guidelines for translating digital pathology applications into clinical practice.