Radiology

Multi-scale and context-aware enhanced YOLOv8 for breast tumor detection in ultrasound images.

Early and accurate detection of breast tumors via ultrasound imaging is paramount for effective clinical intervention. While single-stage object detectors offer vital real-time processing capabilities, their efficacy in the medical domain is severely constrained by spatial information degradation during downsampling, insufficient multi-scale feature representation, and high susceptibility to false...

A hybrid quantum-classical framework for MRI-based deep brain tumor segmentation and classification.

The characterization of brain tumors from magnetic resonance imaging (MRI) is crucial for diagnosis, treatment planning, and prognosis. But the analysis of brain tumors based on MRI is still difficult because of the significant intra-tumoral heterogeneity, ambiguous boundaries of lesions, high dimensionality of imaging features, and complicated nonlinear relationships between anatomical structures...

Serum integrative omics reveals predictive signatures for coronary artery disease.

Identifying serum biomarkers that accurately reflect the progression of coronary artery disease (CAD) remains a major challenge. Integrative proteomic...

Integrating DNA methylation biomarkers for breast cancer risk prediction using artificial intelligence.

Breast cancer remains a major cause of morbidity and mortality among women worldwide, highlighting the necessity for predictive tools to identify at-r...

A predictive model for pathological complete response in neoadjuvant-treated breast cancer: integrating pretreatment clinicopathologic and contrast-enhanced ultrasound characteristics via interpretable machine learning.

BACKGROUND: The ability to predict pathological complete response (pCR) prior to neoadjuvant therapy (NAT) would inform and facilitate tailored therap...

Automated generation of structured breast ultrasound reports using BreastViT and ChatGPT.

BACKGROUND: Breast cancer is the most common malignancy in women. Ultrasound plays a critical role in dense breasts, and BI-RADS provides a standardiz...

Radiomics-Based AI for the Diagnosis and Prognosis of Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma: Systematic Review and Meta-Analysis.

BACKGROUND: Vessels encapsulating tumor clusters (VETCs), a CD34-positive vascular pattern in hepatocellular carcinoma (HCC), are linked to aggressive...

Automated AI-Based Aortic Measurements From Attenuation Correction CT as an Adjunctive Cardiovascular Risk Biomarker: An International Multicenter Study.

BACKGROUND: Aortic enlargement is a powerful predictor of dissection and rupture, yet it is rarely evaluated during routine myocardial perfusion imagi...

Low-Field Neuroimaging: Opportunities and Limitations.

Magnetic resonance imaging (MRI) at low magnetic field strengths (under 1 T) has seen renewed interest, driven by technological advances that enhance ...

Awareness, Educational Needs, and Curriculum Preferences Regarding AI and Medical Big Data Education Among Clinical Medicine Undergraduates: Cross-Sectional Survey Study.

BACKGROUND: The rapid integration of artificial intelligence (AI) and medical big data into health care is transforming diagnosis, treatment planning,...

Retinal imaging for cerebrovascular risk stratification: evidence, limitations, and practical thresholds for the ophthalmologist.

BACKGROUND: The retina shares developmental origin, microvascular anatomy, and barrier physiology with the brain, making non-invasive retinal imaging ...

Comment on "MRI and PET-Based Machine Learning Radiomics for Metastasis Prediction in Pancreatic Ductal Adenocarcinoma: A Systematic Review".

Exploring the Link Between Intravoxel Incoherent Motion Measured Brain Diffusivity During Wakefulness and Sleep Macrostructure in the Elderly.

Intravoxel incoherent motion (IVIM) is a diffusion-weighted magnetic resonance imaging (MRI) method that models slow (D, tissue diffusivity) and fast ...

Transformative Role of Advanced Neural Computation in Clinical Image Diagnostics: A Review of Key Concepts and Applications.

Medical imaging plays a crucial role in modern diagnostic practices, but traditional techniques often face limitations in accuracy, efficiency, and sc...

Early Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer using a Longitudinal US-based Stack-model.

RATIONALE AND OBJECTIVES: To evaluate the diagnostic performance of a longitudinal ultrasound (US)-based stack-model for early prediction of pathologi...

BoneCoT: multicentre validation of a whole-body skeleton foundation model for bone metastases guided by clinician-derived chain of thought.

Given the rising incidence of bone metastases, computed tomography is widely used worldwide as the initial imaging modality for their detection. Accur...

Machine learning algorithms in the estimation of sex from 3DCT-generated cranial and pelvic measurements.

Sex estimation from skeletal remains is a key component of forensic anthropology, with the skull and pelvis being the most sexually dimorphic elements...

An adaptive attention U-network for recognizing ultrasound images.

ObjectiveThe traditional method of intraspinal anesthesia relies on surface anatomical landmarks for positioning, which is associated with a low accur...

Systematic Review and Exploratory Meta-Analysis of AI-Enabled and Digital Technology-Assisted Interventions for Dental Anxiety During Dental Treatment.

BACKGROUND: Dental anxiety adversely affects receiving dental care when needed. Artificial intelligence (AI)-enabled and digital technology-assisted i...

A-eye: Automated 3D MRI segmentation and morphometric feature extraction for eye and orbit atlas construction.

In this study we introduce automated 3D segmentation of the healthy human adult eye and orbit from Magnetic Resonance Images, to improve ophthalmic di...