Artificial Intelligence (AI) has emerged as a transformative force in healthcare, revolutionizing clinical decision support systems. This study aimed to investigate the significant role that AI-powered clinical decision support systems play in shaping nursing practices, particularly on diagnosis and treatment planning. The study employs a comprehensive review of literature on AI-driven clinical decision support systems within nursing. Various sources, including academic papers, healthcare reports, and case studies from five databases namely ScienceDirect, ProQuest, EBSCO, Google Scholar, and PubMed, were analyzed to understand the scope and effectiveness of these systems. AI-powered clinical decision support systems have demonstrated a remarkable ability to enhance the accuracy of nursing diagnoses and the efficiency of treatment planning. These systems, by processing vast volumes of patient data, can identify patterns and correlations that may not be immediately apparent to human nurses. They aid in risk assessment, suggest evidence-based care interventions, and improve overall patient outcomes. The integration of AI in nursing practice, through clinical decision support systems, has the potential to significantly augment the quality of patient care. While these systems do not replace the role of nurses, they act as valuable tools in supporting the decisionmaking process. They can reduce diagnostic errors, save time, and assist in the design of more personalized treatment plans. This study emphasizes the need for AI-driven clinical decision support system research in nursing. To realize AI's potential advantages in nursing diagnosis and treatment planning, nursing practitioners and institutions must embrace these technologies, educate the workforce, and adapt to the changing technological environment.

Keywords: Artificial Intelligence, Clinical Decision, Support Systems, GameChanger, Systematic Review of Literatures, Nursing Practice 

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