AI-driven data analysis in healthcare: Transforming patient care and operational efficiency

Bhimavarapu, Meghana (2025) AI-driven data analysis in healthcare: Transforming patient care and operational efficiency. World Journal of Advanced Engineering Technology and Sciences, 15 (1). pp. 256-263. ISSN 2582-8266

The integration of artificial intelligence in healthcare has revolutionized data analysis approaches, and the article fundamentally transforms patient care delivery and operational efficiency. It examines how AI technologies enable healthcare organizations to effectively process vast quantities of diverse clinical data, including electronic health records, medical imaging, genomic information, and monitoring device outputs. Key applications explored include clinical decision support systems that enhance predictive capabilities, advanced diagnostic tools that augment medical imaging analysis, and operational enhancements that streamline administrative functions. It also addresses significant implementation challenges, including data privacy concerns, algorithmic bias considerations, integration with legacy systems, and ethical dimensions of AI deployment in clinical settings. Despite these obstacles, AI-driven healthcare analytics demonstrate remarkable potential to improve diagnostic accuracy, personalize treatment approaches, optimize resource allocation, and reduce administrative burden—ultimately enhancing both clinical outcomes and healthcare accessibility.