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A Novel Deep Learning-based Artificial Intelligence System for Interpreting Urolithiasis in Computed Tomography.

European urology focus
BACKGROUND AND OBJECTIVE: Our aim was to develop an artificial intelligence (AI) system for detection of urolithiasis in computed tomography (CT) images using advanced deep learning capable of real-time calculation of stone parameters such as volume ...

Predictors of left atrial appendage thrombus in atrial fibrillation patients undergoing cardioversion.

Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing
BACKGROUND: Atrial fibrillation and atrial flutter represent the most prevalent clinically significant cardiac arrhythmias. While the CHA2DS2-VASc score is commonly used to inform anticoagulation therapy decisions for patients with these conditions, ...

Screening for diabetic retinopathy with artificial intelligence: a real world evaluation.

Acta diabetologica
AIM: Periodic screening for diabetic retinopathy (DR) is effective for preventing blindness. Artificial intelligence (AI) systems could be useful for increasing the screening of DR in diabetic patients. The aim of this study was to compare the perfor...

Predicting Survival in Patients with Advanced NSCLC Treated with Atezolizumab Using Pre- and on-Treatment Prognostic Biomarkers.

Clinical pharmacology and therapeutics
Existing survival prediction models rely only on baseline or tumor kinetics data and lack machine learning integration. We introduce a novel kinetics-machine learning (kML) model that integrates baseline markers, tumor kinetics, and four on-treatment...

Motion Artifact Detection for T1-Weighted Brain MR Images Using Convolutional Neural Networks.

International journal of neural systems
Quality assessment (QA) of magnetic resonance imaging (MRI) encompasses several factors such as noise, contrast, homogeneity, and imaging artifacts. Quality evaluation is often not standardized and relies on the expertise, and vigilance of the person...

A robot-based hybrid lower limb system for Assist-As-Needed rehabilitation of stroke patients: Technical evaluation and clinical feasibility.

Computers in biology and medicine
BACKGROUND: Although early rehabilitation is important following a stroke, severely affected patients have limited options for intensive rehabilitation as they are often bedridden. To create a system for early rehabilitation of lower extremities in t...

The neural network RTNet exhibits the signatures of human perceptual decision-making.

Nature human behaviour
Convolutional neural networks show promise as models of biological vision. However, their decision behaviour, including the facts that they are deterministic and use equal numbers of computations for easy and difficult stimuli, differs markedly from ...

Deep Learning Reconstruction of Accelerated MRI: False-Positive Cartilage Delamination Inserted in MRI Arthrography Under Traction.

Topics in magnetic resonance imaging : TMRI
OBJECTIVES: The radiological imaging industry is developing and starting to offer a range of novel artificial intelligence software solutions for clinical radiology. Deep learning reconstruction of magnetic resonance imaging data seems to allow for t...

Explainable Deep-Learning-Based Gait Analysis of Hip-Knee Cyclogram for the Prediction of Adolescent Idiopathic Scoliosis Progression.

Sensors (Basel, Switzerland)
Accurate prediction of scoliotic curve progression is crucial for guiding treatment decisions in adolescent idiopathic scoliosis (AIS). Traditional methods of assessing the likelihood of AIS progression are limited by variability and rely on static m...

Interpretable machine learning for the prediction of death risk in patients with acute diquat poisoning.

Scientific reports
The aim of this study was to develop and validate predictive models for assessing the risk of death in patients with acute diquat (DQ) poisoning using innovative machine learning techniques. Additionally, predictive models were evaluated through the ...