Cardiovascular

Fusion-Restoration Image Processing Algorithm to Improve the High-Temperature Deformation Measurement

In the deformation measurement of high-temperature structures, image degradation caused by thermal radiation and random errors introduced by heat haze restrict the accuracy and effectiveness of deformation measurement. To suppress thermal radiation and heat haze using fusion-restoration image processing methods, thereby improving the accuracy and effectiveness of DIC in the measurement of high-tem...

GARD: Genomic Data based Drug Repurposing in Head and Neck Cancer with Large Language Model Validation

Background/ObjectivesHead and neck cancer (HNC) represents the seventh most common cancer diagnosis globally, yet current treatments, including surgery, radiation, and immunotherapy, have shown limited improvement in outcomes. Drug repurposing offers a cost-effective strategy to identify new therapeutic options by leveraging existing medications with known safety profiles. Within this study we dev...

Onco-Seg: Adapting Promptable Concept Segmentation for Multi-Modal Medical Imaging

Medical image segmentation remains a critical bottleneck in clinical workflows, from diagnostic radiology to radiation oncology treatment planning. We...

Detecting Batch Heterogeneity via Likelihood Clustering

Batch effects represent a major confounder in genomic diagnostics. In copy number variant (CNV) detection from NGS, many algorithms compare read depth...

Breast cancer early detection and molecular subtype prediction by combination of Raman spectroscopy with deep learning.

Breast cancer is one of the most common tumors in women, and early screening can significantly reduce mortality rates. Meanwhile, accurately identifyi...

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and convolutional neural networks.

PURPOSE: The scarcity of high-quality curated labeled medical training data remains one of the major limitations in applying artificial intelligence s...

Machine learning driven prediction of drug efficacy in lung cancer: based on protein biomarkers and clinical features.

Currently, chemotherapy drugs are the first-line treatment for lung cancer patients, and evaluating their efficacy is of utmost significance. However,...

Deep learning predicts the effect of neoadjuvant chemotherapy for patients with triple negative breast cancer.

BACKGROUND: Triple negative breast cancer (TNBC) is an aggressive subcategory of breast cancer with poor prognosis and high risk of recurrence after t...

Exosomal Gene Biomarkers in Osteosarcoma: Mifepristone as a Targeted Therapeutic Revealed by Multi-Omics Analysis.

Osteosarcoma (OS) is an aggressive bone cancer that mainly occurs in children and adolescents. OS patients are mainly treated with neoadjuvant chemoth...

Real-Time Dose-Guided Radiation Therapy.

Dramatic strides have been made in real-time adaptive radiation therapy, where treating single tumors as dynamic but rigid bodies has demonstrated a h...

Optimization-based image reconstruction regularized with inter-spectral structural similarity for limited-angle dual-energy cone-beam CT.

. Limited-angle dual-energy (DE) cone-beam CT (CBCT) is considered as a potential solution to achieve fast and low-dose DE imaging on current CBCT sca...

Label-free single-cell phenotyping to determine tumor cell heterogeneity in pancreatic cancer in real time.

Resistance to chemotherapy of pancreatic ductal adenocarcinoma (PDAC) is largely driven by intratumoral heterogeneity (ITH) due to tumor cell plastici...

Multitask Deep Learning Based on Longitudinal CT Images Facilitates Prediction of Lymph Node Metastasis and Survival in Chemotherapy-Treated Gastric Cancer.

UNLABELLED: Accurate preoperative assessment of lymph node metastasis (LNM) and overall survival (OS) status is essential for patients with locally ad...

HRProfiler Detects Homologous Recombination Deficiency in Breast and Ovarian Cancers Using Whole-Genome and Whole-Exome Sequencing Data.

UNLABELLED: Breast and ovarian cancers harboring homologous recombination deficiency (HRD) are sensitive to PARP inhibitors and platinum chemotherapy....

Leveraging Whole-Exome Sequencing and Mutational Signatures to Detect Homologous Recombination Deficiency in Cancer.

Homologous recombination is a high-fidelity DNA repair mechanism essential for maintaining genome stability. Impairment of this pathway, often due to ...

Predictive Modeling of Human Skin Deformation and Growth During Tissue Expansion in Postmastectomy Breast Reconstruction.

Breast reconstruction using tissue expanders is the primary treatment option following mastectomy. Although skin growth in response to chronic supra-p...

Radiation and contrast dose reduction in coronary CT angiography for slender patients with 70 kV tube voltage and deep learning image reconstruction.

OBJECTIVE: To evaluate the radiation and contrast dose reduction potential of combining 70 kV with deep learning image reconstruction (DLIR) in corona...

Acquisition and Reconstruction Techniques for Coronary CT Angiography: Current Status and Trends over the Past Decade.

Coronary CT angiography (CCTA) has been widely used as a noninvasive modality for accurate assessment of coronary artery disease (CAD) in clinical set...

Agreement between Routine-Dose and Lower-Dose CT with and without Deep Learning-based Denoising for Active Surveillance of Solid Small Renal Masses: A Multiobserver Study.

Purpose To assess the agreement between routine-dose (RD) and lower-dose (LD) contrast-enhanced CT scans, with and without Digital Imaging and Communi...

Medical management of pancreatic cancer: from personalization to broadening treatment strategies.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most heterogeneous and deadly cancers. This review examines recently implemented strategies to i...