AI IN HEALTHCARE: KEY TESTING OF ML BASED SOLUTIONS FOR ACCURACY AND REGULATORY COMPLIANCE

Paper ID: EIJTEM_2024_11_4_114-122

Author's Name: Pradeesh Ashokan

Volume: 11

Issue: 4

Year: 2024

Page No: 114-122

Abstract:

Constantly changing regulatory landscapes prove difficult for businesses among various industries. Innovative strategies needed to address these great regulatory responsibilities henceforth. Thus, this paper discusses improving the efficiency and accuracy of reporting using machine learning (ML) and artificial intelligence (AI) techniques. AI and ML by organisations may enable rapid capturing of data analysis, trend spotting, and regulatory compliance. This research discusses potential gains, pitfalls, and best practices of the incorporation of AI/ML into the reporting architecture. Insightful recommendation is given from a careful analysis of pertinent studies and case studies on how organizations can optimally engage AI/ML to overcome regulatory complexities and get the right reporting outcome.

Keywords: automation, data analysis, artificial intelligence, machine learning, reporting, regulatory complexity, accuracy, efficiency, and innovation.

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