Radiology

Advancements in Machine Learning for Precision Diagnostics and Surgical Interventions in Interconnected Musculoskeletal and Visual Systems.

Artificial intelligence (AI) is reshaping precision medicine by revealing diagnostic links between ocular biomarkers and systemic musculoskeletal disorders. This review synthesizes clinical evidence on the associations between optical coherence tomography (OCT)-derived parameters, such as retinal nerve fiber layer (RNFL) thinning and choroidal thickness, and conditions including osteoporosis, cerv...

From Visualization to Automation: A Narrative Review of Deep Learning's Impact on Ultrasound-based Median Nerve Assessment.

Ultrasound imaging has emerged as a valuable tool in the diagnosis and management of peripheral nerve disorders. The integration of deep learning with ultrasound technology has shown remarkable potential in enhancing diagnostic accuracy and efficiency. This review focuses on the application of deep learning-based approaches in ultrasound diagnostics for peripheral nerve diseases, with particular e...

Brain age prediction from MRI scans in neurodegenerative diseases.

PURPOSE OF REVIEW: This review explores the use of brain age estimation from MRI scans as a biomarker of brain health. With disorders like Alzheimer's...

iPSC-RPE patch restores photoreceptors and regenerates choriocapillaris in a pig retinal degeneration model.

Dry age-related macular degeneration (AMD) is a leading cause of untreatable vision loss. In advanced cases, retinal pigment epithelium (RPE) cell los...

Multimodal MRI radiomics enhances epilepsy prediction in pediatric low-grade glioma patients.

BACKGROUND: Determining whether pediatric patients with low-grade gliomas (pLGGs) have tumor-related epilepsy (GAE) is a crucial aspect of preoperativ...

A Novel Dynamic Neural Network for Heterogeneity-Aware Structural Brain Network Exploration and Alzheimer's Disease Diagnosis.

Heterogeneity is a fundamental characteristic of brain diseases, distinguished by variability not only in brain atrophy but also in the complexity of ...

Functional and structural brain remodeling in patients with degenerative cervical myelopathy following cervical decompression surgery.

BACKGROUND: Degenerative cervical myelopathy (DCM) represents a prevalent etiology of neurological dysfunction, for which cervical decompression surge...

Optical coherence tomography angiography as a tool for diagnosis and monitoring of sickle cell related eye disease: a systematic review and meta-analysis.

Sickle cell retinopathy (SCR) is an ocular manifestation of sickle cell disease (SCD). In SCR abnormal sickling of erythrocytes is associated with sig...

Estimating brain effective connectivity from time series using recurrent neural networks.

Effective Connectivity (EC) reflects the causal influence between brain regions. Identifying Effective Connectivity Networks (ECN) in the brain can en...

Diagnostic Methods and Biomarkers in Inflammatory Bowel Disease.

Inflammatory bowel disease (IBD) refers to a chronic inflammatory condition involving the GI tract that includes Crohn's disease (CD) and ulcerative c...

Ultrasound Diagnosis of Pelvic Organ Prolapse Using Artificial Intelligence.

The aim of this study was to design a fully automated hybrid AI-based method, combining a convolutional neural network (CNN) and a tree-based model (...

Diagnostic Accuracy of Machine Learning-Assisted MRI for Mild Cognitive Impairment in Parkinson's Disease: A Systematic Review and Meta-Analysis.

To evaluate the diagnostic accuracy of machine learning-assisted magnetic resonance imaging (MRI) in detecting cognitive impairment among Parkinson's ...

Classification of neurodegenerative diseases using brain effective connectivity and machine learning techniques: a systematic review.

BACKGROUND: Effective connectivity (EC) refers to the directional influences or causal relationships between brain regions. In the field of artificial...

An Ultrasound Image-Based Deep Learning Radiomics Nomogram for Differentiating Between Benign and Malignant Indeterminate Cytology (Bethesda III) Thyroid Nodules: A Retrospective Study.

RATIONALE AND OBJECTIVES: Our objective is to develop and validate a deep learning radiomics nomogram (DLRN) based on preoperative ultrasound images a...

Deep Learning with Domain Randomization in Image and Feature Spaces for Abdominal Multiorgan Segmentation on CT and MRI Scans.

Purpose To develop a deep learning segmentation model that can segment abdominal organs on CT and MR images with high accuracy and generalization abi...

Mammography-based artificial intelligence for breast cancer detection, diagnosis, and BI-RADS categorization using multi-view and multi-level convolutional neural networks.

PURPOSE: We developed an artificial intelligence system (AIS) using multi-view multi-level convolutional neural networks for breast cancer detection, ...

A machine learning model using echocardiographic myocardial strain to detect myocardial ischemia.

Coronary functional assessment plays a critical role in guiding decisions regarding coronary revascularization. Traditional methods for evaluating fun...

Lung MRI: Indications, Capabilities, and Techniques- Expert Panel Narrative Review.

Lung MRI provides both structural and functional information across a spectrum of parenchymal and airway pathologies. MRI, using current widely availa...

UKF-based model parameter estimation to localize the seizure onset zone in ECoG.

Drug-resistant epilepsy (DRE) patients typically require surgical intervention or neurostimulation. Therefore, accurate localization of the seizure on...

Exchange of Quantitative Computed Tomography Assessed Body Composition Data Using Fast Healthcare Interoperability Resources as a Necessary Step Toward Interoperable Integration of Opportunistic Screening Into Clinical Practice: Methodological Development Study.

BACKGROUND: Fast Healthcare Interoperability Resources (FHIR) is a widely used standard for storing and exchanging health care data. At the same time,...