Brain Cancer

Focused Ultrasound in Brain Tumors: Mechanisms, Imaging Guidance, and Emerging Clinical Applications.

Focused ultrasound (FUS) is an emerging therapeutic and diagnostic technology in neuro-oncology, offering new strategies for molecular diagnosis, drug delivery, and tumor ablation across a range of brain tumors, including glioblastoma (GBM), brain metastases, and diffuse intrinsic pontine glioma (DIPG). The prognosis for aggressive brain tumors remains poor, despite advances in surgery, radiation,...

Comparing artificial intelligence and physician performance in predicting IDH mutation status in glioma.

Predicting isocitrate dehydrogenase (IDH) mutations in gliomas using magnetic resonance imaging (MRI) is clinically important for treatment planning. This study compared two artificial intelligence (AI) models, GliomaDepth-IDH (ResNet34-based) and GliomaVista-IDH (Vision Transformer-based), with 18 physicians (eight neuroradiologists, five neurosurgeons, and five neurosurgery residents) in predict...

A Novel Nomogram for Predicting Meningioma Grade Based on Radiomics Features and Clinical Characteristics.

OBJECTIVE: This study aimed to develop a predictive model utilizing radiomics features and clinical characteristics to accurately differentiate low-gr...

MRI Deep Learning for Differentiating Glioblastoma, IDH-Wildtype from Central Nervous System Diffuse Large B-cell Lymphoma.

Glioblastoma, IDH-wildtype (GBM) and central nervous system diffuse large B-Cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI...

CTM-DETR-frequency-aware and statistically guided transformer for early infrared forest fire detection.

Early-stage infrared forest fire detection is severely hindered by strong background thermal interference and extremely weak fire radiation signals. E...

Fusion attention-based nasopharyngeal carcinoma segmentation model in predicting the clinical outcome of cervical lymph node residue after IMRT.

BACKGROUND: Deep learning methods have made great progress in the automatic segmentation of nasopharyngeal carcinoma, but challenges remain. PURPOSE: ...

Dual-band graphene-based THz MIMO antenna for 6G-enabled biomedical application using supervised regression machine learning validation.

The exponential increase in wireless data traffic and the growing demand for biomedical sensing have driven the advancement of sophisticated antenna t...

A transformer-based patient-agnostic tumor motion tracking model (TransTracking): A feasibility study in radiotherapy for lung cancer.

BACKGROUND: Accurate and real-time localization of thoracic tumor targets is essential for effective radiation therapy. Recently, Transformer architec...

Deep Learning-Based Augmented Contrast-Enhancement and Denoising for Reduced-Iodine and Low-Radiation 70-kVp Cerebral CT Angiography: A Prospective Study.

OBJECTIVE: To evaluate the feasibility of cerebral computed tomography angiography (CTA) obtained with reduced iodine and low radiation at 70 kVp and ...

CBFI: A multi-layer gene network key node identification algorithm integrating structural-biological features and dynamic regulatory weights.

OBJECTIVE: Identifying key nodes within multi-layer GRNs is crucial for uncovering potential biomarkers and therapeutic targets. Key nodes exhibit bot...

Revolutionizing lung cancer screening: the rise of artificial intelligence integrating circulating tumor markers.

Lung cancer persists as the predominant oncological cause of mortality globally, underscoring an imperative public health issue that demands effective...

Mutational signatures in blood-brain barrier: mechanisms, computational insights, and clinical applications in precision oncology.

The blood - brain barrier (BBB) plays a central role in maintaining central nervous system (CNS) homeostasis, and its disruption is a defining feature...

Multi-Omics and Machine Learning-Uncovered FLT1-Mediated Epithelial-Endothelial Crosstalk in Cellular Senescence Driving Clear Cell Renal Cell Carcinoma Malignancy.

Clear cell renal cell carcinoma (ccRCC) is distinguished by the absence of definitive diagnostic markers and efficacious treatment modalities, factors...

Predicting survival of Hodgkin lymphoma using machine learning-an analysis based on the SEER database.

OBJECTIVES: This study aimed to develop an effective model for predicting Hodgkin lymphoma (HL) prognosis as to assist clinicians in making optimal cl...

Revolutionizing nanosatellites' data integrity with SEEnet: A real-time ensemble learning approach for Single-Event Effect (SEE) prediction.

As nanosatellites make access to space more affordable and widespread, protecting onboard data from radiation-related damage has become a major challe...

Application of a machine learning-based PANoptosis-immune-related gene risk score model in prognostic stratification and immunotherapy benefit prediction for glioblastoma.

This study developed a risk score model using PANoptosis and immune-related genes to predict glioblastoma (GBM) prognosis. Utilizing TCGA data and 66 ...

Multi-Institutional Annotated Multiparametric MRI Dataset of Pediatric High-Grade Gliomas.

Pediatric brain tumors are rare and still represent the most common solid tumors in children and the leading cause of cancer-related mortality in the ...

Deep Learning for Survival Prediction in Glioblastoma: Time-dependent Model Interpretability Using MRI, Clinical, and Molecular Data.

Purpose To develop a multimodal model for survival prediction and time-dependent model interpretability in glioblastoma by integrating preoperative MR...

An advanced hybrid deep learning framework for high-precision brain tumor detection and classification in MRI scans.

Early and accurate identification of brain tumors from magnetic resonance imaging (MRI) is essential for timely clinical intervention; however, manual...

A cross-sectional protocol for experimental tongue high-density surface electromyography to detect and classify radiation-associated hypoglossal neuropathy.

BACKGROUND: Hypoglossal neuropathy is the most common lower cranial neuropathy detected as a delayed sequelae of Human Papillomavirus (HPV) -driven or...