AI-Driven Approaches to Streamline and Automate Healthcare Processes
Keywords:
Artificial Intelligence, Healthcare Automation, Machine Learning, Process Optimization, Clinical Decision Support, Electronic Health Records, Predictive Analytics, Data Privacy, Author Name, Scopus, Springer, Journal Name, Wissira, Journal Short Form, Wissira Press, Wissira Research Lab, Research Gate, SSRN, ISSN, Academia, UGC Care, PubMed, WOSAbstract
The advent of Artificial Intelligence (AI) in healthcare has precipitated a transformative shift in how medical services are delivered and managed. AI-driven approaches are rapidly evolving to streamline and automate complex healthcare processes, from patient triage and diagnostics to personalized treatment planning and administrative management. This manuscript examines the integration of AI into healthcare systems, emphasizing its role in automating routine processes, enhancing clinical decision-making, and reducing operational inefficiencies. A systematic review of current literature is combined with empirical analysis of case studies and pilot projects to elucidate both the benefits and challenges associated with AI applications in healthcare settings. Key findings indicate significant improvements in diagnostic accuracy, workflow optimization,and resource allocation when AI technologies are effectively implemented. However, issues such as data privacy, algorithmic transparency, and integration with legacy systems remain pertinent. The study concludes by outlining future research directions and policy implications necessary for harnessing AI’s full potential while ensuring ethical and equitable healthcare delivery.
