Abstract
This paper provides a systems-level evaluation of how artificial intelligence (AI) is integrated into hospital operational infrastructures and how such integration impacts care delivery models. Through a synthesis of empirical studies and systemic analyses, we explore how AI-driven solutions optimize scheduling, triage, diagnostics, and patient flow management. Using structured frameworks and key performance indicators (KPIs) such as hospital throughput, patient satisfaction, and clinical outcomes, we evaluate AI's capacity to transform traditional healthcare models. Our review reveals both significant efficiency gains and ongoing ethical and structural challenges in AI adoption.
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