Nephrology

Deep learning for the prediction of acute kidney injury after coronary angiography and intervention in patients with chronic kidney disease: a model development and validation study.

BACKGROUND: Patients with chronic kidney disease (CKD) are considered the primary population at risk...

Processing Mobility Data Through Artificial Intelligence Can Identify Patterns of Physical Activity in Liver Transplant Candidates.

Deep learning radiomics for the prediction of epidermal growth factor receptor mutation status based on MRI in brain metastasis from lung adenocarcinoma patients.

BACKGROUND: Early and accurate identification of epidermal growth factor receptor (EGFR) mutation st...

Contrast-Induced Acute Kidney Injury in Lower Limb Percutaneous Transluminal Angioplasty: A Machine Learning Approach for Preoperative Risk Prediction.

BACKGROUND: Contrast-induced acute kidney injury (CI-AKI) is a common complication of lower limb per...

A machine learning approach to predict mortality and neonatal persistent pulmonary hypertension in newborns with congenital diaphragmatic hernia. A retrospective observational cohort study.

UNLABELLED: Congenital diaphragmatic hernia (CDH) has high morbidity and mortality rates. This study...

Prediction of Hypertension in the Pediatric Population Using Machine Learning and Transfer Learning: A Multicentric Analysis of the SAYCARE Study.

OBJECTIVE: To develop a machine learning (ML) model utilizing transfer learning (TL) techniques to p...

Early prediction of cardiovascular events following treatments in female breast cancer patients: Application of real-world data and artificial intelligence.

• Application of real-world data and artificial intelligence in detecting cardiotoxicity following c...

Intelligent risk stratification of hypertension based on ambulatory blood pressure monitoring and machine learning algorithms.

. Risk stratification of hypertension plays a crucial role in the treatment decisions and medication...

Identification of Novel Fourth-Generation Allosteric Inhibitors Targeting Inactive State of EGFR T790M/L858R/C797S and T790M/L858R Mutations: A Combined Machine Learning and Molecular Dynamics Approach.

Targeted therapy with an allosteric inhibitor (AIs) is an important area of research in patients wit...

Role of oxidative balance score in staging and mortality risk of cardiovascular-kidney-metabolic syndrome: Insights from traditional and machine learning approaches.

OBJECTIVES: To evaluate the roles of oxidative balance score (OBS) in staging and mortality risk of ...

Machine learning enhanced immunologic risk assessments for solid organ transplantation.

The purpose of this study was to enhance the prediction of solid-organ recipient and donor crossmatc...

Machine-learning assisted discovery unveils novel interplay between gut microbiota and host metabolic disturbance in diabetic kidney disease.

Diabetic kidney disease (DKD) is a serious healthcare dilemma. Nonetheless, the interplay between th...

Development of a natural language processing algorithm to extract social determinants of health from clinician notes.

Disparities in access to the organ transplant waitlist are well-documented, but research into modifi...

GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools-A Pilot Study.

Cell-mediated immunity and chronic inflammation are hallmarks of chronic kidney disease (CKD). Growt...

Bing chat for kidney stone management questions based on the AUA guidelines: a comparison of chatbot conversation style modes.

PURPOSE: Artificial intelligence (AI) technology will inevitably permeate healthcare. Bing Chat is a...

Identification of ALDH2 as a novel target for the treatment of acute kidney injury in kidney transplantation based on WGCNA and machine learning algorithms and exploration of its potential mechanism of action using animal experiments.

BACKGROUND: Acute kidney injury (AKI) after kidney transplantation is one of the main causes of graf...

Machine learning-based risk predictive models for diabetic kidney disease in type 2 diabetes mellitus patients: a systematic review and meta-analysis.

BACKGROUND: Machine learning (ML) models are being increasingly employed to predict the risk of deve...

Risk of major cardiovascular, renal, and thromboembolic events in patients with systemic sclerosis: A longitudinal cohort analysis.

Machine Learning-Based Identification of Novel Exosome-Derived Metabolic Biomarkers for the Diagnosis of Systemic Lupus Erythematosus and Differentiation of Renal Involvement.

OBJECTIVE: This study aims to investigate the exosome-derived metabolomics profiles in systemic lupu...

Estimation of Ganciclovir Exposure in Adults Transplant Patients by Machine Learning.

INTRODUCTION: Valganciclovir, a prodrug of ganciclovir (GCV), is used to prevent cytomegalovirus inf...

Biomarker and clinical data-based predictor tool (MAUXI) for ultrafiltration failure and cardiovascular outcome in peritoneal dialysis patients: a retrospective and longitudinal study.

OBJECTIVES: To develop a machine learning-based software as a medical device to predict the enduranc...