Application of artificial intelligence in renal disease

Abstract

Artificial intelligence (AI) has been applied widely in almost every area of our daily lives, due to the growth of computing power, advances in methods and techniques, and the explosion of data, it also plays a critical role in academic disciplines, medicine is not an exception. AI can augment the intelligence of clinicians in diagnosis, prognosis, and treatment decisions. Kidney disease causes great economic burden worldwide, with both acute kidney injury and chronic kidney disease bringing about high morbidity and mortality. Outstanding challenges in nephrology may be addressed by leveraging big data and AI. In this review, we summarized advances in machine learning (ML), artificial neural network (ANN), convolution neural network (CNN) and deep learning (DL), with a special focus on acute kidney injury (AKI), chronic kidney disease (CKD), end-stage renal disease (ESRD), dialysis, kidney transplantation and nephropathology. AI may not be anticipated to replace the nephrologists’ medical decision-making for now, but instead assisting them in providing optimal personalized therapy for patients.

Keywords

• Artificial intelligence (AI)
• Machine learning (ML)
• Artificial neural network (ANN)
• Convolution neural network (CNN)
• Nephrology