Leveraging Artificial Intelligence for Enhanced Diagnostics in Healthcare: A Comprehensive Approach

Abstract

Artificial intelligence (AI) has emerged as a transformative force in the healthcare industry, offering unprecedented opportunities for improving diagnostics, patient care, and operational efficiency. This paper presents a novel framework for integrating AI-driven techniques into diagnostic workflows, focusing on deep learning models, natural language processing (NLP), and real-time decision support systems. Experimental validation across various medical datasets, including radiology, pathology, and electronic health records (EHRs), demonstrates significant improvements in diagnostic accuracy, speed, and reliability. The study highlights the potential of AI to bridge gaps in healthcare delivery, emphasizing ethical considerations and strategies for scalability in diverse clinical settings.