Nephrology

Cardiovascular Risk Assessment Tools in Chronic Kidney Disease.

Cardiovascular (CV) risk calculators estimate the likelihood of CV events by integrating factors suc...

Radiomics for the Prediction of Postoperative Chronic Kidney Disease in Renal Tumor Patients undergoing Surgical Resection.

OBJECTIVE: Chronic kidney disease (CKD) is a significant concern following renal tumor surgery, impa...

Challenging a clinical dogma with multimodal machine learning: a retrospective analysis of transplant mismatched donor selection.

Advances in the postoperative care of the liver transplant recipient.

PURPOSE OF REVIEW: Survival rates following liver transplantation now exceed 90% at one year. Howeve...

Risk prediction in IgA nephropathy: from conventional models to machine learning, deep learning, and precision nephrology.

IgA nephropathy (IgAN) is the most prevalent primary glomerular disease worldwide and a leading caus...

Machine learning-driven computational drug repurposing to identify new tubulin inhibitors against cancer.

Tubulin is a validated anticancer target, yet the clinical translation of colchicine-binding site in...

Urinary metal exposure, systemic inflammation, and advanced cardiovascular-kidney-metabolic syndrome risk in US adults.

To examine inflammatory biomarkers as potential mediators in the association between urinary metal e...

Factors Associated with Machine Learning-Based Predictions of Retinal Aging Using Teleretinal Screening Images from Patients with Diabetes.

PURPOSE: To identify factors associated with accelerated retinal aging based on machine learning pre...

Development and internal validation of machine learning in predicting prognosis of acute kidney injury patients in resource-limited setting.

BACKGROUND: Machine learning models for predicting acute kidney injury (AKI) prognosis have primaril...

The Rise of Aqueous Selenium-Based Batteries: Challenges, Strategies, and the Path Forward.

Aqueous metal-selenium batteries (AMSeBs) have emerged as promising candidates for safe, cost-effect...

Predicting recurrent cardiac arrest within one year after surviving In-Hospital Cardiac Arrest using a machine learning model.

BACKGROUND: Patients discharged alive after in-hospital cardiac arrest (IHCA) have an increased mort...

Comment on "Machine learning survival analysis for predicting kidney disease progression in patients with acute kidney injury undergoing continuous kidney replacement therapy: An analysis of the LINKA database".

Machine Learning Models for Posttransplant Lymphoproliferative Disorder (PTLD) Risk Prediction in Thoracic Transplantation.

Posttransplant lymphoproliferative disorder (PTLD) is the second most common malignancy in thoracic ...

Interpretable deep learning model of circulating genomics for quantitative survival prediction in advanced non-small cell lung cancer.

PURPOSE: Accurate quantitative survival prediction in advanced non-small cell lung cancer (NSCLC) re...

Developing and validating a machine learning model for predicting post-thrombolysis seizures in acute ischemic stroke.

Post-stroke seizures (PSS) manifests variably due to ischemic brain injury, yet its risk factors rem...

Few-Shot Pulmonary Vessel Segmentation based on Tubular-Aware Prompt-Tuning.

Segmentation of the pulmonary vessel from computed tomography (CT) images plays a crucial role in th...

Flow-driven left ventricular remodelling in long-term haemodialysis: a multicenter model of arteriovenous access-induced cardiac load.

BACKGROUND: Arteriovenous (AV) access, an essential component of dialysis treatment, has been implic...

Using human-robot interaction to assess emotion recognition in dialysis patients: A preliminary study.

This cross-sectional observational study examined the relationship between psychological factors and...

Non-coding RNAs as prognostic biomarkers in autoimmune disease.

Autoimmune diseases comprise a broad spectrum of disorders in which both the innate and adaptive bra...

Prediction of the low-temperature properties of electrolyte solvents for lithium-ion batteries via machine learning.

Electrolytes with low melting points (MPs), high boiling points (BPs), and high dielectric constants...

Factors influencing long-term outcomes in lung transplantation: effective monitoring and comprehensive intervention.

PURPOSE OF REVIEW: Achieving long-term survival after lung transplantation remains a major challenge...