An Adoption Of Artifical Intelligence(Ai) Technology For Patient- Centric Healthcare Solutions

Abstract

The adoption of artificial intelligence (AI) in healthcare is still in its early stages. AI-powered diagnosis, decision support systems, predictive analytic tools, and remote patient monitoring devices can improve treatment plans, reduce costs, and enhance the patient’s experience. Objective: To analyze AI technology adoption and how healthcare professionals create personalized treatment journeys based on unique patient profiles by utilizing AI for more effective and specialized intervention. Method: The research obtained 399 peer-reviewed papers from the Scopus& Web of Science database further SLR, Bibliometric analysis through VoS viewer is used to analyze. Findings: The research states that artificial intelligence (AI), especially in machine learning and natural language processing, holds promise for improving predictive analytics and diagnostic accuracy. These results highlight AI’s capacity to interpret enormous volumes of medical data. It identifies AI in patient-centric solutions will improve healthcare outcomes, lower costs, and improve the entire patient experience, bringing in an innovative era of healthcare delivery. However, challenges identified in AI adoption are data accuracy, Patient privacy, trust, consistency, and relevance. Conclusion: AI technology adoption in healthcare highlights its revolutionary potential for patient-centric solutions. The research highlights how transformational AI may be in empowering people and influencing the direction of personalized, high-quality healthcare in the future. Through the identification and resolution of recognized difficulties, as well as the use of AI-driven insights will move toward a healthcare ecosystem that is patient-centric and improves everyone's quality of life.