Author(s) :

Satish.

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Abstract :

The early detection of infections is a critical challenge in modern medicine, as timely intervention is key to preventing disease progression and complications. Traditional diagnostic approaches, which focus on identifying specific pathogens, can sometimes be slow and are not always effective in detecting infections in their early stages. Advances in artificial intelligence (AI) and microbiome research offer a promising solution for improving early infection detection. The microbiome, a complex community of microorganisms residing within and on the human body, plays a pivotal role in maintaining health and influencing disease outcomes. When disrupted, the balance of the microbiome, referred to as dysbiosis, can signal the onset of various infectious diseases. AI techniques can analyze host-microbiome interactions to identify early biomarkers of infection, even before clinical symptoms appear. This article explores how AI is being used to analyze microbiome data for early infection detection, discusses the potential applications, and addresses the challenges and opportunities in this field.

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