Seminars in Dialysis

Artificial intelligence enabled applications in kidney disease.

Sheetal Chaudhuri, Andrew Long, Hanjie Zhang, Caitlin Monaghan, John W. Larkin, Peter Kotanko, Shashi Kalaskar, Jeroen P. Kooman, Frank M. van der Sande, Dr. Frank Maddux, Len Usvyat

Artificial intelligence (AI) is considered as the next natural progression of traditional statistical techniques. Advances in analytical methods and infrastructure enable AI to be applied in health care. While AI applications are relatively common in fields like ophthalmology and cardiology, its use is scarcely reported in nephrology. We present the current status of AI in research toward kidney disease and discuss future pathways for AI. The clinical applications of AI in progression to end‐stage kidney disease and dialysis can be broadly subdivided into three main topics: (a) predicting events in the future such as mortality and hospitalization; (b) providing treatment and decision aids such as automating drug prescription; and (c) identifying patterns such as phenotypical clusters and arteriovenous fistula aneurysm. At present, the use of prediction models in treating patients with kidney disease is still in its infancy and further evidence is needed to identify its relative value. Policies and regulations need to be addressed before implementing AI solutions at the point of care in clinics. AI is not anticipated to replace the nephrologists’ medical decision‐making, but instead assist them in providing optimal personalized care for their patients.

About the Contributors

Dr. Peter Kotanko, MD

RRI Research Director

SVP, Corporate Research & Development

Peter Kotanko, MD is Research Director at the Renal Research Institute (RRI), New York. Prior to joining RRI, from 1997 to 2007 he served as Vice Chair of a department of internal medicine at an academic teaching hospital in Graz, Austria. Prior to moving to Graz in 1989, he worked 1982-89 at the Department of Physiology and the University Clinic of Internal Medicine, Innsbruck, Austria...

Hanjie Zhang, MSc, PhD

Supervisor of Biostatistics and Applied Artificial Intelligence /Machine Learning

Hanjie joined the RRI in 2014. She received a Master’s Degree in statistics from Columbia University, New York and a PhD in Medical Science from the University of Maastricht, The Netherlands. Hanjie has been involved in the design of several large cluster-randomized clinical trials and complex statistical analyses in collaboration with the Medical Office, FMCNA...