Radiology

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

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Classification of Alzheimer disease using DenseNet-201 based on deep transfer learning technique.

Alzheimer's disease (AD) is a brain illness that causes gradual memory loss. AD has no treatment and...

Accelerated chemical shift encoded cardiovascular magnetic resonance imaging with use of a resolution enhancement network.

BACKGROUND: Cardiovascular magnetic resonance (CMR) chemical shift encoding (CSE) enables myocardial...

Houston, We Have AI Problem! Quality Issues with Neuroimaging-Based Artificial Intelligence in Parkinson's Disease: A Systematic Review.

In recent years, many neuroimaging studies have applied artificial intelligence (AI) to facilitate e...

A Generalisable Heartbeat Classifier Leveraging Self-Supervised Learning for ECG Analysis During Magnetic Resonance Imaging.

Electrocardiogram (ECG) is acquired during Magnetic Resonance Imaging (MRI) to monitor patients and ...

H-Net: Heterogeneous Neural Network for Multi-Classification of Neuropsychiatric Disorders.

Clinical studies have proved that both structural magnetic resonance imaging (sMRI) and functional m...

Uncertainty Estimation and Out-of-Distribution Detection for Deep Learning-Based Image Reconstruction Using the Local Lipschitz.

Accurate image reconstruction is at the heart of diagnostics in medical imaging. Supervised deep lea...

Long-term Major Adverse Cardiac Event Prediction by Computed Tomography-derived Plaque Measures and Clinical Parameters Using Machine Learning.

Objective The present study evaluated the usefulness of machine learning (ML) models with the corona...

Machine learning analysis of contrast-enhanced ultrasound (CEUS) for the diagnosis of acute graft dysfunction in kidney transplant recipients.

AIM: The aim of the study was to develop machine learning algorithms (MLA) for diagnosing acute graf...

The impact of deep learning on diagnostic performance in the differentiation of benign and malignant thyroid nodules.

AIMS: This study aims to use deep learning (DL) to classify thyroid nodules as benign and malignant ...

Deep Learning for Distinguishing Mucinous Breast Carcinoma From Fibroadenoma on Ultrasound.

PURPOSE: Mucinous breast carcinoma (MBC) tends to be misdiagnosed as fibroadenomas (FA) due to its b...

Prospective Evaluation of Artificial Intelligence Triage of Intracranial Hemorrhage on Noncontrast Head CT Examinations.

Retrospective studies evaluating artificial intelligence (AI) algorithms for intracranial hemorrhag...

Computer-aided diagnosis for lung cancer using waterwheel plant algorithm with deep learning.

Lung cancer (LC) is a life-threatening and dangerous disease all over the world. However, earlier di...

Brain tumor image segmentation method using hybrid attention module and improved mask RCNN.

To meet the needs of automated medical analysis of brain tumor magnetic resonance imaging, this stud...

Photoacoustic Quantification of Tissue Oxygenation Using Conditional Invertible Neural Networks.

Intelligent systems in interventional healthcare depend on the reliable perception of the environmen...

Deep Generative Adversarial Reinforcement Learning for Semi-Supervised Segmentation of Low-Contrast and Small Objects in Medical Images.

Deep reinforcement learning (DRL) has demonstrated impressive performance in medical image segmentat...

Artificial intelligence in mammography: a systematic review of the external validation.

OBJECTIVE: To conduct a systematic review of external validation studies on the use of different Art...

PET radiomics-based lymphovascular invasion prediction in lung cancer using multiple segmentation and multi-machine learning algorithms.

The current study aimed to predict lymphovascular invasion (LVI) using multiple machine learning alg...

Conceptual review of outcome metrics and measures used in clinical evaluation of artificial intelligence in radiology.

Artificial intelligence (AI) has numerous applications in radiology. Clinical research studies to ev...

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