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@article{172245,
        author = {Varsha Jayaprakash and Akshay Kailasa},
        title = {Advancements in AI and Data Analytics for Optimizing Healthcare Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {2495-2500},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172245},
        abstract = {The integration of artificial intelligence (AI), data analytics, and cloud computing has significantly transformed healthcare systems. By leveraging scalable AI models and machine learning algorithms, healthcare services can be optimized to enhance patient outcomes, streamline operations, and reduce costs. This paper explores the multifaceted role of data analytics in optimizing Medicaid, focusing on predictive analytics, data quality, interoperability, workforce training, and data-driven decision-making. Drawing upon recent studies, this research highlights the transformative potential of AI-driven solutions in healthcare.},
        keywords = {Medicaid Optimization, Predictive Analytics, Artificial Intelligence in Healthcare, Data Interoperability, Cloud Computing in Healthcare, Healthcare Data Management, AI-Driven, Decision Making, Workforce Training in AI, Healthcare Cost Efficiency, Data-Driven Healthcare Solutions.},
        month = {January},
        }