In recent years, biology and precision medicine have benefited from major advancements in
generating large-scale molecular and biomedical datasets and in analyzing those data …

The integration of clinical data, patient derived data, histology and proteomics and genomics
can enhance the work of clinicians in providing more accurate diagnoses and elevating …

A huge array of data in nephrology is collected through patient registries, large
epidemiological studies, electronic health records, administrative claims, clinical trial …

The emergence of artificial intelligence and machine learning (ML) has revolutionized the
landscape of clinical medicine, offering opportunities to improve medical practice and …

Kidney disease is a leading cause of death worldwide. Currently, the diagnosis of kidney
diseases and the grading of their severity are mainly based on clinical features, which do not …

Chronic kidney disease (CKD) is a significant global health challenge that requires timely
detection and accurate prognosis for effective treatment and management. The application …

Artificial intelligence is increasingly being used to improve diagnosis and prognostication for
acute and chronic kidney diseases. Studies with this objective published in 2019 relied on a …

Machine learning provides researchers with the ability to analyze data that were previously
inaccessible. While still burgeoning, several studies show promising results, which will …

In the past decade, there have been tremendous strides in both the large-scale generation
of phenotypic data with the advent of electronic health record (EHR) systems and the …

Within the literature concerning modern machine learning techniques applied to the medical
field, there is a growing interest in the application of these technologies to the nephrological …