Cardiovascular

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining

With the rapid development of digital pathology, virtual staining has become a key technology in multimedia medical information systems, offering new possibilities for the analysis and diagnosis of pathological images. However, existing H&E-to-IHC studies often overlook the cross-channel correlations between cell nuclei and cell membranes. To address this issue, we propose a novel Cross-Channel ...

MoXGATE: Modality-aware cross-attention for multi-omic gastrointestinal cancer sub-type classification

Cancer subtype classification is crucial for personalized treatment and prognostic assessment. However, effectively integrating multi-omic data remains challenging due to the heterogeneous nature of genomic, epigenomic, and transcriptomic features. In this work, we propose Modality-Aware Cross-Attention MoXGATE, a novel deep-learning framework that leverages cross-attention and learnable modalit...

Analytical Reconstruction of Periodically Deformed Objects in Time-resolved CT

Time-resolved CT is an advanced measurement technique that has been widely used to observe dynamic objects, including periodically varying structure...

Boolean-network simplification and rule fitting to unravel chemotherapy resistance in non-small cell lung cancer

Boolean networks are powerful frameworks for capturing the logic of gene-regulatory circuits, yet their combinatorial explosion hampers exhaustive a...

Future Applications of Cardiothoracic CT.

Radiologists are witnessing astonishing innovation and advancement of CT technologies and their clinical applications. This review highlights how phot...

Chinese acupoint therapies in cancer pain management: research advances and future perspectives.

Cancer pain management (CPM) is crucial in oncology care, with current approaches including pharmacotherapy, radiotherapy, chemotherapy, nerve blocks,...

Automated field-in-field planning for tangential breast radiation therapy based on digitally reconstructed radiograph.

BACKGROUND: The tangential field-in-field (FIF) technique is a widely used method in breast radiation therapy, known for its efficiency and the reduce...

Drug-Drug interactions and special considerations in breast cancer patients treated with CDK4/6 inhibitors: A comprehensive review.

Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) have reshaped the treatment paradigm of hormone receptor positive (HR + )/HER2-negative breast cancer...

AGCLNDA: Enhancing the Prediction of ncRNA-Drug Resistance Association Using Adaptive Graph Contrastive Learning.

Non-coding RNAs (ncRNAs), which do not encode proteins, have been implicated in chemotherapy resistance in cancer treatment. Given the high costs and ...

Radiation oncology patients' perceptions of artificial intelligence and machine learning in cancer care: A multi-centre cross-sectional study.

AIM: The use of artificial intelligence (AI) and machine learning (ML) is increasingly widespread in radiation oncology. However, patient engagement t...

Ultra-Sparse-View Cone-Beam CT Reconstruction-Based Strictly Structure-Preserved Deep Neural Network in Image-Guided Radiation Therapy.

Radiation therapy is regarded as the mainstay treatment for cancer in clinic. Kilovoltage cone-beam CT (CBCT) images have been acquired for most treat...

Wrist and elbow fracture detection and segmentation by artificial intelligence using point-of-care ultrasound.

PURPOSE: Distal radius (wrist) and supracondylar (elbow) fractures are common in children presenting to Pediatric Emergency Departments (EDs). These f...

Role of artificial intelligence -based machine learning model in predicting HER2/neu gene status in breast cancer.

Our study investigated the predictive efficacy of AI-based Machine Learning (ML) model for determining HER2 status in a population of 3424 breast canc...

Self-HER2Net: A generative self-supervised framework for HER2 classification in IHC histopathology of breast cancer.

Breast cancer is a significant global health concern, where precise identification of proteins like Human Epidermal Growth Factor Receptor 2 (HER2) in...

Dimensional Synthesis of 6-DOF Parallel Robot for Intra-Operative Radiation Therapy.

BACKGROUND: In order to meet the kinematic requirements of large range of motion, payload, and stiffness of Intra-Operative Radiation Therapy robots, ...

Prediction methodology of air absorbed dose rates for Chinese cities with deep learning models.

Air absorbed dose rate is a key indicator of environmental radiation exposure. In China, automated environmental radiation monitoring systems have bee...

Deciphering the mechanism of baicalein in cervical cancer via bioinformatics, machine learning and computational simulations: PIM1 and CDK2 are key target proteins.

Cervical cancer is one of the leading causes of death among women worldwide. Current treatments are limited by chemoresistance and chemotherapeutic ag...

Driving Knowledge to Action: Building a Better Future With Artificial Intelligence-Enabled Multidisciplinary Oncology.

Artificial intelligence (AI) is transforming multidisciplinary oncology at an unprecedented pace, redefining how clinicians detect, classify, and trea...

Integrating bulk RNA-seq and scRNA-seq analyses with machine learning to predict platinum response and prognosis in ovarian cancer.

Platinum-based therapy is an integral part of the standard treatment for ovarian cancer. However, despite extensive research spanning several decades,...

Mammogram mastery: Breast cancer image classification using an ensemble of deep learning with explainable artificial intelligence.

Breast cancer is a serious public health problem and is one of the leading causes of cancer-related deaths in women worldwide. Early detection of the ...