Artificial Intelligence for scientific research and discoveries

Abstract

The integration of artificial intelligence (AI) into scientific research is accelerating rapidly, with large language models (LLMs) and generative AI tools now widely adopted by researchers worldwide. While the most common use of LLMs is primarily to enhance written outputs, emerging uses like streamlining systematic reviews and improving research efficiency, with some AI-assisted workflows demonstrating over 350-fold acceleration while maintaining expert-level quality. Beyond text, AI is increasingly applied in drug and protein target discovery, enabling rapid identification of previously inaccessible targets and accelerating early-stage drug development. In medical imaging, multimodal AI models have shown the ability to detect pathologies such as glaucoma from fundus photographs with high accuracy, and generative models can create high-quality, medical-grade images to augment datasets, aid training, and produce educational figures. Despite potential risks, the benefits of these technologies are becoming increasingly evident, with AI poised to transform research methodology, diagnostics, and medical education.

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