Leveraging Artificial Intelligence for Predictive Insights from Healthcare Data
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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Informative Article | Information Technology | United States of America | Volume 13 Issue 10, October 2024 | Popularity: 5.3 / 10


     

Leveraging Artificial Intelligence for Predictive Insights from Healthcare Data

Jaishankar Inukonda


Abstract: Artificial intelligence applications have emerged as a transformative force for healthcare, offering predictive insights to improve patient outcomes, efficient resource utilization, and personalized medicine. The health sector has hugely transformed in modern times with the advent of digital technologies. Artificial Intelligence, conventionally uprooting how health data is used, means major transformative innovations. AI lets massive dimensions of healthcare data transform into actionable insights that can drive better patient outcomes, operational efficiencies, and innovation in medical research. This paper reviews the state of the art for artificial intelligence applications in predictive analytics in healthcare, several machine learning techniques, data types used, and real - world implementation. We discuss challenges and considerations, including those related to data privacy, ethics, and transparency issues, and outline some future directions that may be of benefit in unleashing the full potential of AI across healthcare settings.


Keywords: Healthcare data, AI, Artificial Intelligence, Predictive Insights, Machine learning, Patient outcomes, personalized medicine, Operational Efficiency, Data Privacy and Security, Healthcare Technology


Edition: Volume 13 Issue 10, October 2024


Pages: 611 - 615


DOI: https://www.doi.org/10.21275/SR241006040947



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Jaishankar Inukonda, "Leveraging Artificial Intelligence for Predictive Insights from Healthcare Data", International Journal of Science and Research (IJSR), Volume 13 Issue 10, October 2024, pp. 611-615, https://www.ijsr.net/getabstract.php?paperid=SR241006040947, DOI: https://www.doi.org/10.21275/SR241006040947

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