Nephrology

Latest AI and machine learning research in nephrology for healthcare professionals.

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Interpretable CT Radiomics-based Machine Learning Model for Preoperative Prediction of Ki-67 Expression in Clear Cell Renal Cell Carcinoma.

RATIONALE AND OBJECTIVES: To develop and externally validate interpretable CT radiomics-based machin...

Harnessing NLP to investigate biomarker interactions and CVD risks in elderly chronic kidney disease patients.

Chronic kidney disease (CKD) significantly increases the risk of CVD diseases, particularly among el...

The effect of renal function on the clinical outcomes and management of patients hospitalized with hyperglycemic crises.

BACKGROUND: The global prevalence of diabetes has been rising rapidly in recent years, leading to an...

Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study.

OBJECTIVES: Sufficient attention has not been given to machine learning (ML) models using longitudin...

DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure.

INTRODUCTION: Heart failure (HF) has a very high prevalence in patients with maintenance hemodialysi...

A Comprehensive Review of Artificial Intelligence (AI) Applications in Pulmonary Hypertension (PH).

Pulmonary hypertension (PH) is a complex condition associated with significant morbidity and mortal...

Survival machine learning methods for mortality prediction after heart transplantation in the contemporary era.

Although prediction models for heart transplantation outcomes have been developed previously, a comp...

Partial-Label Contrastive Representation Learning for Fine-Grained Biomarkers Prediction From Histopathology Whole Slide Images.

In the domain of histopathology analysis, existing representation learning methods for biomarkers pr...

A novel RFE-GRU model for diabetes classification using PIMA Indian dataset.

Diabetes is a long-term condition characterized by elevated blood sugar levels. It can lead to a var...

Curcumin nanocrystals ameliorate ferroptosis of diabetic nephropathy through glutathione peroxidase 4.

OBJECTIVE: The aim of this study was to investigate the effect of curcumin nanocrystals (Cur-NCs) on...

Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugs.

We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in...

Dual-Stage AI Model for Enhanced CT Imaging: Precision Segmentation of Kidney and Tumors.

OBJECTIVES: Accurate kidney and tumor segmentation of computed tomography (CT) scans is vital for di...

Major Adverse Kidney Events in Hospitalized Older Patients With Acute Kidney Injury: Machine Learning-Based Model Development and Validation Study.

BACKGROUND: Acute kidney injury (AKI) is a common complication in hospitalized older patients, assoc...

Non-invasive ML methods for diagnosis of congenital heart disease associated with pulmonary arterial hypertension.

OBJECTIVE: Congenital heart disease with pulmonary arterial hypertension (CHD-PAH), caused by CHD, i...

PFSH-Net: Parallel frequency-spatial hybrid network for segmentation of kidney stones in pre-contrast computed tomography images of dogs.

Kidney stone is a common urological disease in dogs and can lead to serious complications such as py...

Artificial Intelligence and Machine Learning in Preeclampsia.

Preeclampsia is a multisystem hypertensive disorder that manifests itself after 20 weeks of pregnanc...

Artificial Intelligence-Guided Inverse Design of Deployable Thermo-Metamaterial Implants.

Current limitations in implant design often lead to trade-offs between minimally invasive surgery an...

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