The growth of artificial intelligence in promoting healthcare is rapidly progressing.
Notwithstanding its promising nature, however, AI in healthcare embodies certain ethical …

Background Acute kidney injury (AKI) is independently associated with morbidity and
mortality in a wide range of surgical settings. Nowadays, with the increasing use of …

Results We identified 4001 patients with sepsis-associated AKI. We utilized 2546 combined
features for K-means clustering, identifying three subphenotypes. Subphenotype 1 had 1443 …

Chronic kidney disease (CKD) has become a major global health crisis, causing millions of
yearly deaths. Predicting the possibility of a person being affected by the disease will allow …

Rationale & Objective Risk prediction tools for assisting acute kidney injury (AKI)
management have focused on AKI onset but have infrequently addressed kidney recovery …

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 …

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 …

This study explores the contemporary landscape of integrating numerical algorithms,
artificial intelligence (AI), and expert methodologies within the domain of nephrology …

The convergence of AI and machine learning (ML), electronic health records (EHRs), the
Internet of Things (IoT), and enhanced data transfer and accessibility has within the last …

Background Artificial intelligence (AI) has rapidly advanced in the medical field, leveraging
its intelligence and automation for the management of various diseases. Brain arteriovenous …