Introduction Machine learning has been increasingly used to develop predictive models to
diagnose different disease conditions. The heterogeneity of the kidney transplant population …

Recent advances in surgical, immunosuppressive and monitoring protocols have led to the
significant improvement of overall one-year kidney allograft outcomes. Nonetheless, there …

Kidney diseases form part of the major health burdens experienced all over the world.
Kidney diseases are linked to high economic burden, deaths, and morbidity rates. The great …

Background Liver transplantation, the last treatment for advanced liver failure, necessitates
patient education due to its wide range of complications and subsequent disabilities. The …

The use of artificial intelligence and machine learning (ML) has revolutionized our daily lives
and will soon be instrumental in healthcare delivery. The rise of ML is due to multiple factors …

A key issue in the field of kidney transplants is the analysis of transplant recipients' survival.
By means of the information obtained from transplant patients, it is possible to analyse in …

Background Obesity is a multifaceted condition that impacts individuals across various age,
racial, and socioeconomic demographics, hence rendering them susceptible to a range of …

An increasing number of studies claim machine learning (ML) predicts transplant outcomes
more accurately. However, these claims were possibly confounded by other factors, namely …

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 …

Background The variations in outcome and frequent occurrence of kidney allograft failure
continue to pose important clinical and research challenges despite recent advances in …