Integrating Artificial Intelligence into Chronic Kidney Disease Care: Enhancing Hemodialysis Scheduling, Comorbidity Management, and Diagnostic Capabilities:

Raniah I. Alnaser; Mohammed N. Abed; Fawaz A. Alassaf; Mohammad H. Alsaaty

doi:10.33192/smj.v77i7.274440

Authors

Raniah I. Alnaser Nineveh Health Directorate, Mosul, Nineveh province, 41006, Iraq
Mohammed N. Abed University of Mosul, College of Pharmacy, Department of Clinical Laboratory Sciences, Mosul, Nineveh province, 41002, Iraq
Fawaz A. Alassaf University of Mosul, College of Pharmacy, Department of Pharmacology and Toxicology, Mosul, Nineveh province, 41002, Iraq
Mohammad H. Alsaaty 4Department of Medicine, College of Medicine, University of Mosul, Mosul, Nineveh province, 41002, Iraq

DOI:

https://doi.org/10.33192/smj.v77i7.274440

Keywords:

Chronic kidney disease, Hemodialysis, Artificial intelligence

Abstract

Chronic kidney disease (CKD) is one of the most common and serious illnesses affecting individuals worldwide, potentially leading to kidney failure. Various strategies exist to manage CKD, with hemodialysis being the most effective. However, this treatment comes with numerous limitations that can significantly affect patients’ quality of life. Therefore, it is crucial to explore new approaches to address these challenges. Recently, artificial intelligence (AI) has emerged as a promising tool in nephrology. This review aims to reduce the need for frequent dialysis and to explore the future potential of AI in the field of nephrology. The frequency of hemodialysis refers to the regular, scheduled dialysis sessions mainly prescribed for patients with CKD, in addition to the unplanned or premature initiation of hemodialysis through predictive and preventive interventions. This narrative review systematically searched Google Scholar and PubMed using keywords related to CKD, hemodialysis, and AI. AI is used in kidney disease to predict CKD progression, evaluate drug prescriptions, detect medical errors, adjust dialysis schedules, and identify unknown comorbidities and phenotypes. Integrating AI in nephrology holds promise for reducing kidney dialysis frequency through its applications in the management plans of patients with CKD.

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