Current status and challenges of artificial intelligence in digital pathology diagnosis
LI Yan
Abstract：Pathological diagnosis occupies a central position in precision medicine, and its accuracy and efficiency are crucial for disease treatment and patient prognosis. In recent years, with the rapid development of digital pathology and computer vision algorithms, artificial intelligence (AI) has gradually attracted widespread attention in tumor pathology diagnosis and has achieved significant results. AI technology simulates human thinking and decision-making processes through deep learning algorithms, which can significantly improve the efficiency and accuracy of pathological diagnosis, especially in key areas such as tumor diagnosis, disease prediction, and prognosis evaluation, showing a very broad application prospect. AI diagnosis based on big data not only enables personalized management of patients but also demonstrates significant advantages in speed and accuracy in the diagnosis of common diseases. This article comprehensively summarizes the latest research progress in the field of AI in pathology diagnosis, analyzes the feasibility of its application, deeply discusses the challenges faced in the field of digital pathology, and looks forward to future development trends.
Keywords：Artificial IntelligenceDigital PathologyPathological DiagnosisAuxiliary Diagnosis
Publication Date：2025-12-28
Online Publishing Date：2026-01-28(First online date of this platform, not the publication date of the document)
Pages：5( 1692-1696 )