Histological Analysis of Zoonotic Diseases and Artificial Intelligence

Zoonotic diseases remain major global public health challenges, requiring rapid, accurate, and scalable diagnostic approaches. Histological tissue analysis is fundamental for identifying the pathological features of zoonotic infections, but manual microscopy is limited by low throughput, observer variability, and shortages of specialist expertise. This chapter examines how artificial intelligence (AI), particularly deep learning-based image analysis, is transforming the histological diagnosis of zoonotic diseases such as tuberculosis, brucellosis, and leishmaniasis within the One Health framework. It evaluates AI models for histopathological and cytological image analysis, explores applications in cross-species surveillance and geospatial disease monitoring, and discusses challenges related to implementation, explainability, and clinical adoption. The chapter concludes by outlining future directions for standardized, transparent, and accessible AI-driven veterinary histopathology.

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