Optimizing Healthcare Delivery with AGI Strategies for Enhancing Provider Network Performance
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Analysis Study Research Paper | Information Technology | United States of America | Volume 13 Issue 8, August 2024 | Popularity: 4.8 / 10


     

Optimizing Healthcare Delivery with AGI Strategies for Enhancing Provider Network Performance

Umamaheswara Reddy Kudumula


Abstract: The healthcare sector in the United States faces numerous challenges, including evolving patient needs, regulatory pressures, administrative burdens, and a shortage of healthcare professionals, especially in underserved areas. This paper explores the transformative potential of Artificial Intelligence (AI) to address these critical issues. By leverAIng AI's capabilities in predictive analytics, workflow automation, and clinical decision support, healthcare systems can significantly improve resource management, enhance patient care quality, and streamline operational processes. We provide a comprehensive framework for integrating AI within healthcare, focusing on applications in predictive modeling, clinical diagnostics, patient engagement, and administrative automation [1]. The paper also addresses the technological, infrastructural, ethical, and data privacy considerations essential for the successful deployment of AI in healthcare.


Keywords: Cognitive Computing, Predictive Modeling, Clinical Efficiency, Automated Decision-Making, Personalized Health Solutions, Data Security, Privacy, Ethical AI


Edition: Volume 13 Issue 8, August 2024


Pages: 474 - 478


DOI: https://www.doi.org/10.21275/SR24808094614



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Umamaheswara Reddy Kudumula, "Optimizing Healthcare Delivery with AGI Strategies for Enhancing Provider Network Performance", International Journal of Science and Research (IJSR), Volume 13 Issue 8, August 2024, pp. 474-478, https://www.ijsr.net/getabstract.php?paperid=SR24808094614, DOI: https://www.doi.org/10.21275/SR24808094614

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