Journal of Pathology Informatics· 2026Q1· Review
A new era in computational pathology: A survey on foundation and vision-language models
- 2citations
- Q1SCImago
- 2026year
Short summary
Foundation Models (FMs) and Vision-Language Models (VLMs) are revolutionizing computational pathology (CPath) by enabling diagnostic workflows that leverage vast datasets without explicit supervision and integrate natural language reports for improved predictions.
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Key points
- Foundation Models (FMs) enable adaptable representation learning for various downstream tasks in CPath without explicit supervision.
- Vision-Language Models (VLMs) utilize natural language pathology reports as rich semantic information sources.
- FMs and VLMs can improve existing CPath models and generate predictions in natural language.
- The survey systematically reviews recent innovations, tools, datasets, and training schemes for FMs and VLMs in CPath.
AI-generated from the title and abstract; the full text is not read.
Abstract
Recent advances in deep learning have completely transformed the domain of computational pathology (CPath). More specifically, it has altered the diagnostic workflow of pathologists by integrating foundation models (FMs) and vision-language models (VLMs) in their assessment and decision-making process. The limitations of existing deep learning approaches in CPath can be overcome by FMs through learning a representation space that can be adapted to a wide variety of downstream tasks without explicit supervision. Deploying VLMs allow pathology reports written in natural language be used as rich semantic information sources to improve existing models as well as generate predictions in natural language form. In this survey, a holistic and systematic overview of recent innovations in FMs and VLMs in CPath is presented. Furthermore, the tools, datasets, and training schemes for these models are summarized in addition to categorizing them into distinct groups. This extensive survey highlights the current trends in CPath and its possible revolution through the use of FMs and VLMs in the future.
The authors' abstract, as published at the source. Journal of Pathology Informatics, 2026 · DOI ↗
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Field: Artificial Intelligence
Artificial IntelligenceComputer Science