Clinical Research and Artificial Intelligence: How AI Is Changing Clinical Research

Abstract

Medicine is quickly transitioning as artificial intelligence (AI) adopts the new and improved type of machine learning for better diagnosis and treatment of diseases in the various sub-specialties of practice. The enhancement of computation rate raises the potential of AI algorithms and their value for multiple domains like radiology, where some experts suppose that AI can replace radiologists. These questions are essential when determining whether specific AI applications will eventually replace doctors or only assist them in their work within specific medical specialties. This paper ponders the iridescent role of AI in clinical trials and how its drug invention process will result from innovative learning in the future. The technology engages the role of AI in clinical decision support, the latest developments in precision medicine, and the prediction of drug properties and active ingredients. The paper showcases AI contributions to remodeling clinical trial designs and model exchange and using AI to carry out the intervention. Among other things, it speaks about AI in the acquisition of the EHR, in the course of authorization of the trial, and in addressing some of the significant challenges such as data availability and perpetual vigilance. In addition, a few discussions concerning clinical AI algorithm errors and the defects of conventional trial procedures are also incorporated at the end of the paper to portray the role of AI in present clinical research more sharply.

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