Breast Cancer

Clinical knowledge constrained multi-task learning framework for breast cancer diagnosis using ultrasound videos.

Ultrasound is widely used in breast cancer diagnosis due to its cost-effectiveness, non-invasiveness, and radiation-free properties. Computer-aided diagnostic systems based on dynamic breast ultrasound videos have advanced rapidly. However, existing methods are often affected by redundant information, make limited use of clinical prior knowledge, and provide insufficiently interpretable diagnostic...

Applications of bioimpedance measurement in clinical and allied fields: a comprehensive review.

BACKGROUND: Accurate and timely disease detection is essential in modern healthcare. Conventional imaging methods such as computed tomography (CT), magnetic resonance imaging (MRI), and dual-energy X-ray absorptiometry (DXA) offer valuable diagnostic information, but face significant limitations, including high cost, radiation exposure, and lengthy scan times. Electrical impedance tomography (EIT)...

Artificial intelligence classification of spatial CD8 + T-cell distribution on computed tomography in oropharyngeal cancer.

CD8 + T-cell presence and distribution in oropharyngeal cancer (OPC) reflects specific immune phenotypes and are linked to prognosis. Image processing...

Multicenter validation and randomized crossover reader evaluation of deep learning-assisted tri-sequence three-dimensional MRI segmentation for hypopharyngeal tumor.

BACKGROUND AND PURPOSE: Accurate MRI-based target delineation for hypopharyngeal squamous cell carcinoma (HPSCC) is clinically important but expertise...

Unraveling the Multifunctional and Translational Paradigm of Nanoparticulate Systems against Colorectal Cancer.

Colorectal cancer (CRC) is a health burden due to its high mortality rate, recurrence rate, and drug resistance. The limitations of traditional method...

Advanced Data Analytics and Machine Learning for Geospatial Interpolation, Anomaly Detection, Background Prediction and Emergency Evacuation Routing in Real-Time Radiation Monitoring System.

For identifying natural trends, hotspots, hazardous areas, and mitigating potential health risk to the public and environment, spatial analysis of rad...

An interpretable machine learning model integrating [18F]FDG PET/CT radiomics and clinical features for predicting perforation following chemotherapy in gastrointestinal lymphoma: a multicenter study.

BACKGROUND: Perforation following chemotherapy in gastrointestinal lymphoma (PFCGL) is a rare but severe and life-threatening complication. Early pre-...

Artificial Intelligence for Molecular Subtyping in Unresectable Gallbladder Cancer: A Proof-of-Concept Study for CT-based HER2 Status Prediction.

BACKGROUND/AIMS: Human epidermal growth factor receptor 2 (HER2) overexpression is a critical therapeutic target in gallbladder cancer (GBC), but dete...

Artificial intelligence integrated multi-omics and multimodal studies promote the efficacy of neoadjuvant chemotherapy in breast cancer: opportunities, challenges, and future perspectives.

BACKGROUND: Neoadjuvant chemotherapy (NAC) is a critical therapeutic strategy for locally advanced breast cancer; however, its clinical utility is con...

From data to decision: a clinical pipeline for wearable AI in early cardiotoxicity detection.

Chemotherapy-induced cardiotoxicity (CIC) is a leading cause of morbidity in cancer survivors, as conventional surveillance often detects cardiac dysf...

Radiation biomarker screening and dose reconstruction based on machine learning.

PURPOSE: Nuclear emergency medical rescue is a critical component of the nuclear emergency response system, playing a vital role in safeguarding publi...

Beyond gross total resection (GTR): Deep peritumoral radiomics for predicting overall survival (OS) and O6-methylguanine-DNA-methyltransferase promoter methylation (MGMTpm) status in glioblastoma multiforme.

BACKGROUND & OBJECTIVE: Glioblastoma Multiforme (GBM) is an aggressive and highly heterogeneous brain tumor with poor survival outcomes. While convent...

Calcite nanoparticles as advanced, pH-responsive platforms for cancer therapy: a comprehensive and critical review.

Nanomedicine offers powerful opportunities to overcome the pharmacokinetic and microenvironmental limitations of conventional chemotherapy, particular...

What are the views of cancer care administrators and clinicians in England on the use of a machine learning clinical decision support system (ML-CDSS) to predict patients' risk of hepatic and renal deterioration during chemotherapy? A qualitative study.

OBJECTIVE: To explore administrators' and clinicians' views on the factors that influence their use and adoption of a machine learning clinical decisi...

Automatic computation of breast cancer biomarkers from multiple [Formula: see text] F-FDG PET image segmentation.

Neoadjuvant chemotherapy is a standard clinical practice for tumor downsizing in breast cancer, with [Formula: see text]F-FDG Positron Emission Tomogr...

Dendrobine inhibits the growth and invasion of human breast cancer cells by regulating the NF-κB signaling pathway via the SLC6A9 target.

Dendrobine exhibits notable anti-tumor activity against breast cancer (BRCA). In this study, we integrated network pharmacology, bioinformatics, and e...

Machine learning-driven integration of multi-omics data uncovers methylation-dependent molecular signatures for luminal A and B breast cancer subtypes.

BACKGROUND: Breast cancer is the most common malignancy in women and includes molecular subtypes with distinct clinical outcomes, such as luminal A an...

Artificial intelligence iterative imaging reconstruction with low-dose CT scans for hepatic metastases.

Contrast-enhanced CT is commonly used in the evaluation of hepatic metastatic lesions. This prospective study aimed to assess the capability of artifi...

Coxmos: interpretable survival models for high-dimensional and multi-omic data.

BACKGROUND: Survival analysis in high-dimensional (HD) and multi-block (MB) settings, such as omic and multi-omic studies, poses major methodological ...

Efficacy of short-course bevacizumab for brain tumor radiation necrosis with a volumetric analysis.

PURPOSE: Radiation necrosis (RN) is a challenging complication of cranial irradiation, often requiring corticosteroids for management. This study eval...