AI in biomedical research: unleashing the potential of a transformative partnership

Abstract

Biomedical Science research, by its very nature, generates colossal volumes of data ranging from genomics to medical imaging, that is both complex and diverse. It demands a lot of time and expertise to translate that data into meaningful interpretations to be applied on the bedside. AI algorithms on the other hand, possess the exceptional ability to examine this wealth of information, uncovering patterns and relationships. It has been claimed that it may elude even the most astute human minds1 in some areas of social sciences. The interpretation of data in the field of Biomedical research, however, remains debatable2. Nonetheless, it can accelerate the pace of scientific discovery, enabling researchers to identify novel therapeutic targets, understand disease mechanisms, and develop innovative treatments. Moreover, the resounding question that echoes across laboratories and research institutions globally is not whether AI can be employed in biomedical research, but instead, how extensively we can tap into its complete potential. The integration of AI into Biomedical Sciences is yet not free from its set of challenges. Privacy concerns and ethical considerations related to data usage must be diligently addressed. Additionally, robust validation and transparency in AI models are essential to ensure their reliability and safety3. continue...