Nephrology

RACGAP1 is a pivotal gene in lung adenocarcinoma-associated membranous nephropathy: Based on comprehensive bioinformatics analysis and machine learning.

BACKGROUND: This study performs a detailed bioinformatics and machine learning analysis to investiga...

Multi-parametric MRI-based machine learning model for prediction of pathological grade of renal injury in a rat kidney cold ischemia-reperfusion injury model.

BACKGROUND: Renal cold ischemia-reperfusion injury (CIRI), a pathological process during kidney tran...

Artificial intelligence in chronic kidney diseases: methodology and potential applications.

Chronic kidney disease (CKD) represents a significant global health challenge, characterized by kidn...

Unlocking Tomorrow's Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial Intelligence.

As an integral aspect of health care, digital technology has enabled modelling of complex relationsh...

Machine learning for the prediction of 1-year mortality in patients with sepsis-associated acute kidney injury.

INTRODUCTION: Sepsis-associated acute kidney injury (SA-AKI) is strongly associated with poor progno...

Artificial intelligence meets pulmonary hypertension: early detection for a late-presenting disease.

Creatinine clearance in critically ill adults: prospective comparison of prediction by intensive care unit physicians and machine learning models.

Risk prediction of kalaemia disturbance and acute kidney injury after total knee arthroplasty: use of a machine learning algorithm.

INTRODUCTION: Total knee arthroplasty (TKA) is a procedure associated with risks of electrolyte and ...

A Boundary-Enhanced Decouple Fusion Segmentation Network for Diagnosis of Adenomatous Polyps.

Adenomatous polyps, a common premalignant lesion, are often classified into villous adenoma (VA) and...

Machine learning-based prediction of vancomycin concentration after abdominal administration in patients with peritoneal dialysis-related peritonitis.

INTRODUCTION: Peritonitis is a serious complication of peritoneal dialysis (PD), in which insufficie...

STC-UNet: renal tumor segmentation based on enhanced feature extraction at different network levels.

Renal tumors are one of the common diseases of urology, and precise segmentation of these tumors pla...

The Current Application and Future Potential of Artificial Intelligence in Renal Cancer.

Artificial intelligence (AI) is the integration of human tasks into machine processes. The role of A...

Automated identification and segmentation of urine spots based on deep-learning.

Micturition serves an essential physiological function that allows the body to eliminate metabolic w...

Transforming Hypertension Diagnosis and Management in The Era of Artificial Intelligence: A 2023 National Heart, Lung, and Blood Institute (NHLBI) Workshop Report.

Hypertension is among the most important risk factors for cardiovascular disease, chronic kidney dis...

Brief Review and Primer of Key Terminology for Artificial Intelligence and Machine Learning in Hypertension.

Recent breakthroughs in artificial intelligence (AI) have caught the attention of many fields, inclu...

Automatically Detecting Pancreatic Cysts in Autosomal Dominant Polycystic Kidney Disease on MRI Using Deep Learning.

BACKGROUND: Pancreatic cysts in autosomal dominant polycystic kidney disease (ADPKD) correlate with ...

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, ...

Smell cancer by machine learning-assisted peptide/MXene bioelectronic array.

Non-invasive detection of tumors is of utmost importance to save lives. Nonetheless, identifying tum...

Development of a machine learning-based model for the prediction and progression of diabetic kidney disease: A single centred retrospective study.

BACKGROUND: Diabetic kidney disease (DKD) is a diabetic microvascular complication often characteriz...

Habitat radiomics and deep learning fusion nomogram to predict EGFR mutation status in stage I non-small cell lung cancer: a multicenter study.

Develop a radiomics nomogram that integrates deep learning, radiomics, and clinical variables to pre...

Data modeling analysis of GFRP tubular filled concrete column based on small sample deep meta learning method.

The meta-learning method proposed in this paper addresses the issue of small-sample regression in th...