Cardiovascular

Zero Echo Time Magnetic Resonance Imaging of the Spine.

Zero echo time magnetic resonance imaging is an ultrashort echo time technique that enables computed tomography-like visualization of cortical and trabecular bone while preserving the ionizing radiation-free, multiplanar, and soft tissue advantages of conventional magnetic resonance imaging. This narrative review outlines the technical foundations of spinal zero echo time imaging, such as sequence...

Identification of potential biomarkers and therapeutic targets for liver cirrhosis based on Mendelian randomization and machine learning.

BACKGROUND: Liver cirrhosis(LC) represents the end stage of chronic liver disease, yet reliable molecular markers remain limited. This study aimed to uncover potential diagnostic biomarkers and therapeutic targets for LC. METHODS: We integrated differential gene analysis from LC datasets in the Gene Expression Omnibus (GEO) with Mendelian randomization (MR) using eQTLGen and FinnGen summary data t...

Homologous recombination deficiency in Ovarian cancer: The game-changer for first-line maintenance therapy.

Homologous recombination deficiency (HRD) plays a central role in the pathogenesis and therapeutic vulnerability of epithelial ovarian cancer (EOC), p...

Artificial intelligence-based analysis of thrombotic and infectious risk factors in peripherally inserted central catheters (PICCs).

INTRODUCTION: Peripherally inserted central catheters (PICCs) are increasingly used in France for prolonged intravenous therapies such as chemotherapy...

Optimizing material composition determination in dual-energy computed tomography: a comparative study of a linear model and a fully connected neural network.

Accurate elemental decomposition in dual-energy computed tomography (DECT) is crucial for precision in radiation therapy planning. We present a compar...

Improving visibility of small anatomical details on low and ultra-low dose computed tomography with artificial intelligence-based image reconstructions.

To assess how computed tomography (CT) image reconstruction techniques affect perceived diagnostic image quality at varying radiation dose levels in c...

Functional-based multi-omics early prediction of radiation pneumonitis in NSCLC using AI-generated perfusion and ventilation from planning CT.

ObjectiveThis study aims to develop a functional-based multi-omics model for early prediction of radiation pneumonitis (RP) by extracting radiomic and...

Hulled Rice or husk? Synchrotron radiation XRF and deep learning approach for the determination of the geographical origin of Chinese rice samples.

Accurate authentication of rice geographical origin is crucial for food safety and fraud prevention. Synchrotron radiation X-ray fluorescence (SR-XRF)...

MuTriM: A multiscale deep learning model integrating longitudinal radiomics and pathomic features for predicting recurrence and adjuvant radiation benefit in breast cancer.

PURPOSE: We present MuTriM, a multimodal deep learning model integrating DCE-MRI and whole-slide pathology to predict survival and radiation benefit i...

CT-based radiomics for predicting the treatment response to PD-1/PD-L1 inhibitors combined with chemotherapy in unresectable gastric cancer.

OBJECTIVE: To develop and validate a CT-based radiomics model to predict immunotherapy response in unresectable gastric cancer and explore its underly...

Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit: a multicentre, model development and validation study.

BACKGROUND: Genomic assays such as Oncotype DX have transformed adjuvant treatment selection for hormone receptor-positive, HER2-negative, early breas...

Assessment Tools of Radiation Skin Injury in Head and Neck Cancer: A Narrative Review of Preclinical and Clinical Studies.

Radiation skin injury (RSI) is an unavoidable side effect of radiotherapy that delays the treatment process and affects patients' quality of life. How...

Automatic segmentation of clinical target volume for radiation therapy in breast-conserving patients and exploration of clinical factors influential to its performance.

OBJECTIVES: To develop and validate a deep learning model for whole breast clinical target volume (CTV) contouring and evaluate clinical features affe...

SMC4/SMAD3/NF-κB axis drives cervical cancer progression and radioresistance via DNA damage repair and immune modulation.

OBJECTIVE: Cervical cancer remains a significant global health burden, with the molecular determinants of its progression and therapeutic resistance n...

Uncovering Clinically Relevant Breast Cancer Subtypes Biomarkers Using Integrative Bioinformatics and Machine Learning Approaches.

A precise diagnosis and customized treatment become more difficult by the genomic heterogeneity of breast cancer (BRCA). In order to examine gene expr...

Artificial intelligence-based quantification of breast arterial calcifications to predict cardiovascular morbidity and mortality.

BACKGROUND AND AIMS: Women are underdiagnosed and undertreated for cardiovascular disease (CVD). Automatic quantification of breast arterial calcifica...

Integrative network pharmacology and machine learning identify potential targets of indole-3-lactic acid in colorectal cancer.

The treatment of colorectal cancer (CRC) remains challenging due to chemotherapy resistance and genetic heterogeneity. Indole-3-lactic acid (ILA), a t...

Multimodal Deep Learning-Based Screening of Degenerative Temporomandibular Joint Disease Using 2D Radiography: A Cost-Effective and Low-Radiation Approach.

OBJECTIVES: This study aimed to develop and preliminarily validate a multimodal deep learning model based on two-dimensional maxillofacial imaging for...

Enhancing adverse drug event extraction and summarization for cancer drugs through large language models.

PURPOSE: Cancer treatments such as chemotherapy, targeted therapy, and immunotherapy can effectively combat malignant cells but frequently cause serio...

The dual role of the crosstalk between autophagy and ferroptosis in lung cancer treatment: Advances in mechanisms and therapeutic strategies (Review).

The interaction between autophagy and ferroptosis has resulted in the identification of novel approaches for the treatment of lung cancer (LC). The tw...