Impact of Data Hygiene on AI Performance: A Comprehensive Study in Healthcare Applications
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 14 Issue 4, April 2025 | Popularity: 4.8 / 10


     

Impact of Data Hygiene on AI Performance: A Comprehensive Study in Healthcare Applications

Vinu V Pillai Sobhana


Abstract: Integrating clean data and Artificial Intelligence (AI) in health can completely transform medical diagnosis, therapy, and patient management. Clear data is very important for guaranteeing the validity and dependability of artificial intelligence models, therefore raising their capacity to give accurate medical observations. Still, difficulties including data quality, interoperability, bias, privacy concerns, scalability, and regulatory limits impede the seamless use of artificial intelligence in the medical field. Notwithstanding these hiccups, artificially intelligent healthcare solutions raise diagnostic accuracy, automate administrative works, and allow for personalized medicine. The vital need of artificial intelligence in healthcare data cleaning, its difficulties, and more general ramifications for the healthcare sector are addressed in this article. Maximizing AI's potential and guarantee ethical and secure deployment will depend in part on creative frameworks and rules handling these problems.


Keywords: clean data, artificial intelligence, healthcare transformation, diagnostic accuracy, ethical deployment


Edition: Volume 14 Issue 4, April 2025


Pages: 1140 - 1144


DOI: https://www.doi.org/10.21275/SR25411101305


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Vinu V Pillai Sobhana, "Impact of Data Hygiene on AI Performance: A Comprehensive Study in Healthcare Applications", International Journal of Science and Research (IJSR), Volume 14 Issue 4, April 2025, pp. 1140-1144, https://www.ijsr.net/getabstract.php?paperid=SR25411101305, DOI: https://www.doi.org/10.21275/SR25411101305

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