Radiology

Diagnosis and management of Candida endophthalmitis and chorioretinitis.

BACKGROUND: Candida endophthalmitis (CE) and chorioretinitis are uncommon but potentially devastating complications of candidemia, associated with significant risks of vision loss and long-term morbidity. Effective management relies on timely diagnosis and targeted antifungal therapy. However, diagnostic and therapeutic approaches are hindered by inconsistent guidelines, limited evidence, and vari...

Functional connectome-based predictive modeling of suicidal ideation.

Suicide represents an egregious threat to society despite major advancements in medicine, in part due to limited knowledge of the biological mechanisms of suicidal behavior. We apply a connectome predictive modeling machine learning approach to identify a reproducible brain network associated with suicidal ideation in the hopes of demonstrating possible targets for novel anti-suicidal therapeutics...

An orchestration learning framework for ultrasound imaging: Prompt-Guided Hyper-Perception and Attention-Matching Downstream Synchronization.

Ultrasound imaging is pivotal in clinical diagnostics due to its affordability, portability, safety, real-time capability, and non-invasive nature. It...

Automatic identification of Parkinsonism using clinical multi-contrast brain MRI: a large self-supervised vision foundation model strategy.

BACKGROUND: Valid non-invasive biomarkers for Parkinson's disease (PD) and Parkinson-plus syndrome (PPS) are urgently needed. Based on our recent self...

Cardiac CT for electrophysiological interventions.

Cardiac computed tomography (CCT) holds an important role in the field of electrophysiology offering critical insights that enhance the management of ...

Development of an Open-Source Algorithm for Automated Segmentation in Clinician-Led Paranasal Sinus Radiologic Research.

OBJECTIVE: Artificial Intelligence (AI) research needs to be clinician led; however, expertise typically lies outside their skill set. Collaborations ...

Tilorone attenuates high-fat diet-induced hepatic steatosis by enhancing BMP9-Smad1/5/8 signaling.

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is rapidly increasing and is caused by excessive fat deposition in ...

Evaluation of Diagnostic Recommendations Embedded in Medication Alerts: Prospective Single-Arm Interventional Study.

BACKGROUND: Potentially inappropriate prescribing in outpatient care contributes to adverse outcomes and health care inefficiencies. Clinical decision...

Modeling Brain Aging with Explainable Triamese ViT: Towards Deeper Insights into Autism Disorder.

Machine learning, particularly through advanced imaging techniques such as three-dimensional Magnetic Resonance Imaging (MRI), has significantly impro...

PlaNet-S: an Automatic Semantic Segmentation Model for Placenta Using U-Net and SegNeXt.

This study aimed to develop a fully automated semantic placenta segmentation model that integrates the U-Net and SegNeXt architectures through ensembl...

Development of a No-Reference CT Image Quality Assessment Method Using RadImageNet Pre-trained Deep Learning Models.

Accurate assessment of computed tomography (CT) image quality is crucial for ensuring diagnostic accuracy, optimizing imaging protocols, and preventin...

Automated Body Composition Analysis Using DAFS Express on 2D MRI Slices at L3 Vertebral Level.

Body composition analysis is vital in assessing health conditions such as obesity, sarcopenia, and metabolic syndromes. MRI provides detailed images o...

Mechanisms and management of self-resolving lumbar disc herniation: bridging molecular pathways to non-surgical clinical success.

Spontaneous resorption of lumbar disk herniation (LDH) presents a promising avenue for the non-surgical management of herniated disks. Here we present...

Improving Breast Cancer Diagnosis in Ultrasound Images Using Deep Learning with Feature Fusion and Attention Mechanism.

RATIONALE AND OBJECTIVES: Early detection of malignant lesions in ultrasound images is crucial for effective cancer diagnosis and treatment. While tra...

[Progress of individualized precision therapy for peritoneal metastasis in gastric cancer].

Peritoneal metastasis represents the most aggressive form of gastric cancer metastasis and serves as a primary contributor to poor prognosis. Conventi...

Advances in Diagnostic Approaches for Alzheimer's Disease: From Biomarkers to Deep Learning Technology.

Alzheimer's disease (AD) is a devastating neurological disorder that affects humans and is a major contributor to dementia. It is characterized by cog...

Quantitative computed tomography imaging classification of cement dust-exposed patients-based Kolmogorov-Arnold networks.

BACKGROUND: Occupational health assessment is critical for detecting respiratory issues caused by harmful exposures, such as cement dust. Quantitative...

A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts.

Creating a dataset for training supervised machine learning algorithms can be a demanding task. This is especially true for blood vessel segmentation ...

Deep learning-based automated segmentation for the quantitative diagnosis of cerebral small vessel disease via multisequence MRI.

OBJECTIVE: Existing visual scoring systems for cerebral small vessel disease (CSVD) cannot assess the global lesion load accurately and quantitatively...

Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would.

INTRODUCTION: Emergency rescue scenes and pre-hospital emergency stages commonly encounter trauma victims. Life-saving measures must be taken at the s...