Urology

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

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A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation.

BACKGROUND: Postoperative acute kidney injury (AKI) is a significant risk associated with surgeries ...

QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials.

Accurate prediction of protein-ligand binding affinities is crucial in drug discovery, particularly ...

Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus.

BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetic mellitus ...

[Making prostate cancer research accessible: chatGPT-4 as a tool to enhance lay communication].

BACKGROUND AND OBJECTIVE: The abundant potential arising from various applications of artificial int...

A machine learning model to predict intradialytic hypotension in pediatric continuous kidney replacement therapy.

BACKGROUND: Intradialytic hypotension (IDH) is associated with mortality in adults undergoing interm...

Effects of Renal Function on the Multimodal Brain Networks Affecting Mild Cognitive Impairment Converters in End-Stage Renal Disease.

RATIONALE AND OBJECTIVES: Cognitive decline is common in End-Stage Renal Disease (ESRD) patients, ye...

Machine learning models to predict osteoporosis in patients with chronic kidney disease stage 3-5 and end-stage kidney disease.

Chronic kidney disease-mineral bone disorder is a common complication in patients with chronic kidne...

Identification of biomarkers related to iron death in diabetic kidney disease based on machine learning algorithms.

BACKGROUND: While ferroptosis has been recognised for its key role in tumour development, its involv...

Urinary biomarkers of kidney transplant rejection.

PURPOSE OF REVIEW: Despite the introduction of many new immunosuppressive medications, allograft rej...

An ensemble learning model to predict lymph node metastasis in early gastric cancer.

Lymph node metastasis is a critical factor for determining therapeutic strategies and assessing the ...

Uncertainty quantification for CT dosimetry based on 10 281 subjects using automatic image segmentation and fast Monte Carlo calculations.

BACKGROUND: Computed tomography (CT) scans are a major source of medical radiation exposure worldwid...

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