ARTIFICIAL INTELLIGENCE IN BIOMEDICAL SCIENCES: OPPORTUNITY AND SCOPES

Abstract

In biomedical research and healthcare, artificial intelligence (AI) has emerged as a major disruptive force that improves clinical decision-making processes and allows for more sophisticated analysis of large-scale, complicated biomedical data. AI methods like machine learning (ML) and deep learning (DL) are developing quickly and being used in a variety of biological fields, such as drug development, diagnostics, treatment planning, and disease prediction. The growing amount and complexity of data produced by genomics, imaging, and clinical sources presents difficulties for biomedical research; artificial intelligence (AI) provides effective techniques for identifying significant patterns and insights that conventional methods frequently overlook. AI models have been extensively used in medical imaging for analysis tasks including diagnosis, segmentation, and classification, greatly assisting radiologists and clinicians with automated and accurate picture interpretation.

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