Integrating AI Technology into Biomedical Research and Health Innovation

Abstract

Artificial intelligence (AI) has become a revolutionizing force in biomedical research, providing unprecedented functionality to complex data, simulating biological systems, and facilitating innovation in healthcare delivery. This chapter outlines the uptake of AI technologies ranging from machine learning and deep learning to generative AI, NLP, and federated learning, across the breadth of biomedical science. State-of-the-art tools such as TensorFlow, PyTorch, BioBERT, medGAN, and AlphaFold are described in the context of real-world applications, ranging from disease diagnosis to drug discovery, clinical decision support, personalized medicine, and synthetic data creation. Edge computing for wearables, explainable AI for transparent decision-making, and ethical considerations of privacy and model bias are highlighted. Through case examples and tool-oriented discussion, the chapter illustrates how AI not only accelerates scientific discovery but also improves patient outcomes, particularly in precision health and translational medicine.

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