Author(s) :

Navyashree.

Volume/Issue :

Abstract :

The identification and understanding of emerging zoonotic pathogens are critical to preventing pandemics and managing public health risks. Traditional pathogen discovery and epidemiological surveillance methods are dependent on manual literature reviews, which can be inefficient and inadequate given the sheer volume of scientific literature. Large Language Models (LLMs) present a promising solution for automating the process of literature mining, enabling rapid identification and understanding of zoonotic pathogens. These AI models can process vast amounts of text, extract relevant insights, and generate hypotheses about the ecological, genetic, and epidemiological traits of zoonotic diseases. This paper explores how LLMs can be employed to enhance the study of emerging zoonotic pathogens, focusing on their capabilities, applications, challenges, and potential future directions.

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