Applications and challenges

Abstract

Artificial intelligence (AI) is transforming biomedicine, advancing diagnostics, drug discovery, and personalised medicine. Techniques such as deep learning and robotic surgery are enhancing precision and efficiency, while natural language processing is facilitating the analysis of clinical data. However, challenges such as data quality, algorithmic bias, and clinical integration still require careful attention. It is crucial to balance innovation and regulation, promote interdisciplinary collaboration, and develop transparent and explainable AI systems. The future of AI in biomedicine is promising, but we need an ethical and collective approach to maximise its positive impact on global health.