Journal of Nephrology & Therapeutics

ISSN: 2161-0959

Open Access

Sarah Jones

Department of Nephrology, University of Calgary, Calgary, Canada

  • Mini Review   
    Artificial Intelligence and Machine Learning Applications in Predicting Renal Impairment Progression
    Author(s): Sarah Jones*

    Renal impairment, including chronic kidney disease, represents a significant global health challenge with a growing prevalence. Timely and accurate prediction of renal impairment progression is crucial for effective patient management, resource allocation, and the development of personalized treatment plans. In recent years, artificial intelligence and machine learning have emerged as powerful tools for enhancing our ability to predict and manage renal impairment progression. This research article explores the applications of AI and ML in predicting renal impairment progression, discusses their benefits, challenges, and the future outlook for this transformative field... Read More»
    DOI: 10.37421/2161-0959.2023.13.462

    Abstract HTML PDF

Google Scholar citation report
Citations: 784

Journal of Nephrology & Therapeutics received 784 citations as per Google Scholar report

Journal of Nephrology & Therapeutics peer review process verified at publons

Indexed In

arrow_upward arrow_upward