Brain Cancer

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 technologies, particularly within the terahertz (THz) frequency range. This research presents an innovative graphene-based microstrip patch antenna featuring a slotted design and MIMO configuration, specifically designed for the high-speed needs of 6G...

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 architectures have demonstrated strong global reasoning capabilities across multiple frames by leveraging both self-attention and cross-attention mechanisms. Transformers have therefore been applied to object tracking with great success. By combining Image G...

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...

Machine learning-based disentanglement of meteorological and anthropogenic drivers of ozone pollution in the Chengdu-Chongqing urban agglomeration.

To clarify the relative contributions of meteorological conditions and anthropogenic activities to ozone (O3) pollution in the Chengdu-Chongqing urban...

Beyond binary classification: a pilot study of imaging-derived glioma severity modeling using T1-weighted and diffusion MRI radiomics.

OBJECTIVE: Gliomas are heterogeneous brain tumors with variable biology and treatment response. Accurate, non-invasive assessment of tumor aggressiven...

Glioblastoma region-specific metabolic signatures reflect patient survival duration.

PURPOSE: Spatial metabolic differences found in glioblastoma (GBM) tumor core (contrast enhancing) and peritumoral (T2/FLAIR hyperintense) edge tissue...

Face aging rate quantifies change in biological age to predict cancer outcomes.

Chronological age predicts cancer survival but does not capture differences in biological aging rates. We apply FaceAge, an artificial intelligence al...

Beyond HLA-Ia: A multidimensional framework for Neoantigen immunotherapy.

Glioblastoma (GBM) and other malignant gliomas are associated with aggressive progression, high recurrence rates, and poor long-term outcomes, while c...

Multi-Omics and Machine Learning Analyses Reveal PIK3CG, PRKCD, and TRIM22 as Potential Markers of Poor Prognosis and Immune Activation in Glioblastoma.

BACKGROUND: Glioblastoma (GBM) is one of the most aggressive brain tumors with a poor prognosis despite current treatment modalities. This study aimed...