ARTIFICIAL INTELLIGENCE-BASED APPROACH TO PERFORM MONITORING AND DIAGNOSTIC PROCESS FOR A HOLISTIC ENVIRONMENT

Jeshwanth Reddy Machireddy

Authors

Jeshwanth Reddy Machireddy Senior software Developer, IT, KForce, Madison, Wisconsin, USA Author

Keywords:

Artificial intelligence, Implementation science, Change management, Information systems, Digital technology

Abstract

The optimization of pharmaceutical products is the focus of recent advances in digital medicine methods. The pharmaceutical sector could benefit greatly from artificial intelligence (AI) in several ways, including accelerated product development, improved product quality, and more efficient therapy. This article provides a comprehensive analysis of the current state of artificial intelligence (AI) in the pharmaceutical product lifecycle. A search was conducted in PubMed and IEEE Xplore for all articles published between January and March of 2022. After screening for relevant outcomes, publication genres, and data sufficiency, 73 papers (1.2%) were kept out of 6131. To conduct the systematic review and meta-analysis, we followed the guidelines laid out by the PRISMA statement. By the very nature of their implementation, all AI systems fall into several overlapping classes. Clinical trials and pre-clinical tests accounted for 34% of the 177 initiatives that utilized AI. New small molecule design systems come in at 33%, putting them in second position. Novel drug target discovery is the third most common area for AI implementation. This feature is available in almost a quarter of the systems. Surprisingly, 102 systems (or 57% of the total) focus only on a single domain. When it comes to functionality and coverage of the lifespan, none of the systems are up to the task. When DR, AMD, and Nevus are detected all at once, our comprehensive AI method achieves a high diagnosis accuracy. Higher sensitivities with little effect on specificity are made possible with the incorporation of pathology-specific algorithms. In addition, it lessens the possibility of overlooking by accident findings.

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