Urology

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

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Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review.

BACKGROUND: With the development of artificial intelligence, the application of machine learning to ...

Single-center outcomes of artificial intelligence in management of pulmonary embolism and pulmonary embolism response team activation.

Multidisciplinary pulmonary embolism response teams (PERTs) have shown that timely triage expedites ...

Multitask learning of a biophysically-detailed neuron model.

The human brain operates at multiple levels, from molecules to circuits, and understanding these com...

Deep-learning-based segmentation using individual patient data on prostate cancer radiation therapy.

PURPOSE: Organ-at-risk segmentation is essential in adaptive radiotherapy (ART). Learning-based auto...

Deep learning identifies histopathologic changes in bladder cancers associated with smoke exposure status.

Smoke exposure is associated with bladder cancer (BC). However, little is known about whether the hi...

The impact of high-order features on performance of radiomics studies in CT non-small cell lung cancer.

High-order radiomic features have been shown to produce high performance models in a variety of scen...

Ppb-Level Ammonia Sensor for Exhaled Breath Diagnosis Based on UV-DOAS Combined with Spectral Reconstruction Fitting Neural Network.

Ammonia (NH) in exhaled breath (EB) has been a biomarker for kidney function, and accurate measureme...

Using machine learning to predict the risk of short-term and long-term death in acute kidney injury patients after commencing CRRT.

BACKGROUND: The mortality rate and prognosis of short-term and long-term acute kidney injury (AKI) p...

Quality of Information About Kidney Stones from Artificial Intelligence Chatbots.

Kidney stones are common and morbid conditions in the general population with a rising incidence gl...

Comparison of data fusion strategies for automated prostate lesion detection using mpMRI correlated with whole mount histology.

BACKGROUND: In this work, we compare input level, feature level and decision level data fusion techn...

Predicting graft and patient outcomes following kidney transplantation using interpretable machine learning models.

The decision to accept a deceased donor organ offer for transplant, or wait for something potentiall...

Using artificial intelligence to generate medical literature for urology patients: a comparison of three different large language models.

PURPOSE: Large language models (LLMs) are a form of artificial intelligence (AI) that uses deep lear...

Prediction of post-donation renal function using machine learning techniques and conventional regression models in living kidney donors.

BACKGROUND: Accurate prediction of renal function following kidney donation and careful selection of...

Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study.

OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS), a systematic method for assessing i...

Clinical-Grade Validation of an Autofluorescence Virtual Staining System With Human Experts and a Deep Learning System for Prostate Cancer.

The tissue diagnosis of adenocarcinoma and intraductal carcinoma of the prostate includes Gleason gr...

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

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

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...

Machine learning computational model to predict lung cancer using electronic medical records.

BACKGROUND: Lung cancer (LC) screening using low-dose computed tomography (CT) is recommended accord...

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