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@article{187144,
        author = {Mrs. R. Sangeetha and Mrs. Sharon Spoorthy D S and Mr. Shashidharan V and Ms. Priyanka G},
        title = {Generative AI in Healthcare: Bridging Clinical Innovation and Organizational Efficiency},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {3680-3696},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187144},
        abstract = {Generative Artificial Intelligence (Gen AI) has rapidly emerged as a transformative force in healthcare, addressing persistent challenges such as clinician burnout, diagnostic inefficiencies, and rising operational costs. This paper presents a comprehensive review of Gen AI’s clinical and administrative applications, emphasizing its role in personalized medicine, synthetic data generation, medical imaging, surgical assistance, nursing support, and pandemic preparedness. Beyond clinical domains, it highlights the technology’s value in medical education, healthcare marketing, and revenue cycle management. By synthesizing recent research and industry developments, the paper identifies how Gen AI enhances decision-making, optimizes workflows, and enables predictive and adaptive healthcare systems. The findings underscore Gen AI’s potential to create more efficient, equitable, and patient-centered healthcare delivery when implemented with strong ethical and governance frameworks.},
        keywords = {Generative AI, Healthcare innovation, Personalized medicine, Clinical efficiency, Large language models, Ethical AI, Health information systems, Medical technology},
        month = {November},
        }