What’s new in digital and computational pathology 2026: advances in adoption, standards, AI technologies, and clinical integration
Digital and computational pathology are expanding rapidly worldwide, driven by advances in whole-slide imaging, AI algorithms, multimodal data integration, and improved digital infrastructure. Adoption continues to accelerate in the United States and internationally, supported by professional guidelines, emerging reimbursement pathways, and the growing need for remote workflows and collaborative diagnostics. Progress in interoperability standards, regulatory frameworks, and FDA approvals has strengthened the foundation for clinical deployment, while large-scale data repositories and federated learning approaches enable more robust and privacy-preserving model development. Foundation models, multimodal AI systems, and LLM-based copilots are reshaping diagnostic support, prognostication, workflow efficiency, clinical trials and drug discovery.
Authors
- Chadi Hajar
- Selim Sevim (ORCID: https://orcid.org/0000-0002-3436-0464)
- Snehal Sonawane (ORCID: https://orcid.org/0000-0003-3384-7702)
Publication Details
- Journal
- Journal of Pathology and Translational Medicine
- Published
- 2026-05-15
- DOI
- https://doi.org/10.4132/jptm.2026.04.27
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00