Cardiovascular

ViT-MultiRAGNet: A scalable and reliable retrieval-augmented Vision Transformer framework for memory-guided feature fusion multi-modal mammogram classification.

BACKGROUND: Diagnosing breast cancer with mammography continues to be an incidentally challenging process because of the numerous different ways of acquiring the images, the vast difference in appearance between lesions, and the minimal use of historical information regarding patients being considered when making a diagnosis. In addition, many current deep learning algorithms use static weight val...

Integrating MRI radiomics and deep learning for predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer: a multicenter study.

OBJECTIVE: Develop a multimodal fusion model combining MRI radiomics and deep learning (DL) to predict pathologic complete response (pCR) in breast cancer patients post-neoadjuvant chemotherapy (NACT). METHODS: Patients with locally advanced breast cancer from two centers (Center 1: 404 training, Center 2: 174 testing) were enrolled. Pretreatment MRI radiomic features and DL-derived features were ...

Pharmacogenomics in oncology: mutation-targeted therapy and biomarker integration in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most common cancer-related cause of death among all countries globally, mostly because of late diagnosis, he...

ProphDR: An Interpretable Deep Learning Model for Predicting Cancer Drug Response via Multi-Omics and Cross-Attention Mechanisms.

Predicting cancer drug responses (CDRs) accurately remains a significant challenge due to the complexity of tumor biology and the limitations of exist...

Treatment-specific CT Radiomics Models To Predict Response To Neoadjuvant Therapy And Explore Individualized Treatment Selection In Gastric Cancer.

RATIONALE AND OBJECTIVES: To develop and compare general and treatment-specific radiomics models based on pretreatment computed tomography (CT) for pr...

Explainable hourly global solar radiation forecasting using a CNN-BiLSTM model with temperature scaled softmax attention.

Accurate global solar radiation (GSR) forecasting is vital for smart grids and resilient energy systems. However, the nonlinear and non-stationary nat...

Reframing Response in Neoadjuvant Chemotherapy for Ovarian Cancer: Integrating Molecular and Functional Biomarkers.

BACKGROUND: Neoadjuvant chemotherapy (NACT) is an established treatment strategy for advanced epithelial ovarian cancer, particularly for patients wit...

Ensemble machine learning for predicting breast cancer recurrence and mortality using clinical and hemogram data.

Accurate prediction of breast cancer recurrence remains difficult because prognosis varies significantly across molecular subtypes. This underscores t...

Topological imaging of single-cell CAF heterogeneity for predicting prognosis and adjuvant chemotherapy benefit in pancreatic cancer.

PURPOSE: Cancer-associated fibroblasts (CAFs) are central drivers of PDAC progression and therapeutic resistance, yet their preoperative clinical util...

Artificial intelligence-based calcium scoring using 3D transesophageal echocardiography in aortic stenosis: a pilot study.

BACKGROUND: Aortic valve calcium scoring by computed tomography (CT) is an established method for assessing aortic stenosis severity but is limited by...

RadiolGAN: Multicenter Feasibility Study of Synthetic CT From 3D Ultra-Short Echo Time MRI for Enhanced Pulmonary Radiologic Sign Visualization.

BACKGROUND: Chest CT requires breath-holding and ionizing radiation. 3D ultrashort echo time (UTE) MRI allows radiation-free imaging, but the image qu...

Antibody-drug conjugates in selected solid tumours: a position statement update based on findings from the third workshop held by the ETOP IBCSG Partners Foundation.

The European Thoracic Oncology Platform (ETOP) International Breast Cancer Study Group (IBCSG) Partners Foundation initiated a series of workshops for...

Center-specific Federated Learning for Radiation Pneumonitis:A Cross-Center Adaptive Alternating Framework.

BACKGROUND AND PURPOSE: Accurate prediction of symptomatic radiation pneumonitis (RP) is critical for radiotherapy, yet the generalization of deep lea...

Role of MRI-based synthetic CT and low-dose CT for the assessment of structural damage in axial spondyloarthritis - a review.

Structural lesions, including erosions, sclerosis, and pathological new bone formation, are key features of disease progression in axial spondyloarthr...

AI-Based Analysis of Tumor-Infiltrating Lymphocytes and Homologous Recombination in Ovarian Cancer: JGOG3025-A1 Study.

Understanding the tumor immune microenvironment, especially tumor-infiltrating lymphocytes (TILs), remains crucial in ovarian cancer. However, the dis...

AI-Optimized 3D-Printed Dual-Layer Implant: Resolving Chemo-Immunotherapy Sequential Administration Dilemma for Colorectal Cancer Peritoneal Metastasis.

The synergistic integration of chemotherapy and immunotherapy represents the most promising strategy for enhancing therapeutic efficacy in cancer trea...

Time-dependent radiological risk assessment following a severe NPP accident using Monte Carlo simulation, BEIR VII, and interpretable AI.

Nuclear reactor accidents can result in prolonged radiation exposure with complex and uncertain health consequences. Existing studies often focus on d...

DFCE-KanT: Predicting Spatial Gene Expression from Histology Images via Contrastive Learning.

MOTIVATION: Spatial transcriptomics (ST) can quantitatively characterize the spatial molecular profile in tissues and yet is costly to be applied at a...

Unveiling the identification of the genetic features and biological characteristics shared between cervical cancer and venous thromboembolism.

OBJECTIVE: The association between cervical cancer (CC) and venous thromboembolism (VTE) has been well documented, but the underlying molecular charac...

Efficient Diagnosis of Spatiotemporal Evolution and Driving Factors of Surface Ozone Pollution Episodes: An Application in Jiangsu Province, China.

Severe ozone (O3) pollution is a major challenge for air quality improvement in China, primarily due to its spatiotemporal heterogeneity and nonlinear...