Digital and artificial intelligence-based pathology: not for every laboratory

Background and objectives

With the increasing use of artificial intelligence (AI) in diagnostics, AI algorithms have shown great potential in aiding diagnostics. As more of these algorithms are developed, there is overwhelming enthusiasm for implementing digital and artificial intelligence-based pathology (DAIP), but doubts and pitfalls are also emerging. However, few original or review articles address the limitations and practical aspects of implementing DAIP. In this review, we briefly examine the evidence related to the benefits and pitfalls of DAIP implementation and argue that DAIP is not suitable for every clinical laboratory.

Methods

We searched the PubMed database using the following keywords: “digital pathology,” “digital AI pathology,” and “AI pathology.”. Additionally, we incorporated personal experiences and manually searched related papers.

Results

Ninety-two publications were found, of which 24 met the inclusion criteria. Many advantages of DAIP were discussed, including improved diagnostic accuracy and equity. However, several limitations of implementing DAIP exist, such as financial constraints, technical challenges, and legal/ethical concerns.

Conclusions

We found a generally favorable but cautious outlook for the implementation of DAIP in the pathology workflow. Many studies have reported promising outcomes in using AI for diagnosis and analysis; however, there are also several noteworthy limitations in implementing DAIP. Therefore, a balance between the benefits and pitfalls of DAIP must be thoroughly articulated and examined in light of the institution’s needs and goals before making the decision to implement DAIP. Approaches for mitigating machine learning biases were also proposed, and the adaptation and growth of the pathology profession were discussed in light of DAIP development and advances.

Full text

https://www.xiahepublishing.com/2771-165X/JCTP-2025-00007

The study was recently published in the Journal of Clinical and Translational Pathology.

Journal of Clinical and Translational Pathology (JCTP) is the official scientific journal of the Chinese American Pathologists Association (CAPA). It publishes high quality peer-reviewed original research, reviews, perspectives, commentaries, and letters that are pertinent to clinical and translational pathology, including but not limited to anatomic pathology and clinical pathology. Basic scientific research on pathogenesis of diseases as well as application of pathology-related diagnostic techniques or methodologies also fit the scope of the JCTP.

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