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

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.