# Artificial intelligence in digital pathology diagnosis and analysis: technologies, challenges, and future prospects

## TL;DR

This paper reviews how AI can transform pathology by analyzing histopathological images, covering technologies, challenges, and future directions for better disease diagnosis.

## Contribution

The paper provides a systematic evaluation of AI applications in pathology and proposes a roadmap for advancing precision oncology.

## Key findings

- AI tools show promise in tumor classification and biomarker discovery in pathology.
- Challenges include noisy annotations and domain shifts in clinical translation of AI models.
- A technical taxonomy and benchmarking of algorithms are presented for diverse diagnostic tasks.

## Abstract

Artificial intelligence (AI) offers transformative potential in pathology, where histopathological images remain the diagnostic gold standard due to their rich morphological and molecular information. While the rapid development of AI-driven computational pathology tools is revolutionizing disease interpretation, these technologies have not yet been systematically evaluated. Therefore, this review systematically evaluates AI applications across the diagnostic continuum, from image preprocessing and tumor classification to prognostic stratification and the discovery of predictive biomarkers. It presents a technical taxonomy of the algorithms and foundation models powering these applications, benchmarking their performance across diverse diagnostic tasks through rigorous comparative analyses. It also identifies critical challenges in clinical translation, including computational scaling, noisy annotations, interpretability gaps, and domain shifts. Finally, it proposes a roadmap for advancing AI applications in precision oncology and pathological research. By bridging technological innovation with clinical needs, this review aims to accelerate the integration of robust, unified, scalable AI solutions into diagnostic workflows.

The online version contains supplementary material available at 10.1186/s40779-025-00680-6.