Introduction
Artificial intelligence (AI) is transforming healthcare across multiple domains, from drug discovery, personalized medicine, and medical diagnostics. In pathology, there is an increasing shift towards digital workflows, with growing evidence that AI-based analysis tools can assist pathologists by improving diagnostic efficiency and inter-rater agreement in clinical biopsy scoring1,2,3. Integrating AI into digital pathology supports a more data-driven, reproducible, and precise approach to cancer diagnostics (Figure 1). As digital pathology gains traction, there is increasing opportunity for pathologists to leverage AI-based image analysis tools for histopathology evaluation and precise tumor quantification for both clinical and research applications. In the clinical setting, AI can enhance diagnostic accuracy, speed, and consistency for faster case prioritization, while in research, AI enables more accurate quantification of tumor content to support more precise sample selection for downstream analyses. By enhancing histopathology evaluation in both domains, AI is helping to drive significant innovation in pathology.
