Association of NID2 gene single nucleotide polymorphisms with glioma risk and prognosis in Chinese Han population Academic Background Glioma is the most common primary intracranial tumor, characterized by high mortality and poor prognosis. Despite some progress in diagnostic and treatment strategies, conventional therapies have limited improvement ...

Useful Features for Overall Survival Prediction in Low-Grade Glioma Patients Academic Background Glioma is a type of neoplastic growth in the brain that usually poses a serious threat to the patients’ lives. In most cases, glioma eventually leads to the death of the patient. The analysis of glioma typically involves examining pathological slices of...

Glioma Disease Prediction Based on Optimized Integrated Machine Learning Background and Research Objectives In medical research, gliomas are the most common type of primary brain tumors, encompassing various cancer types with different clinical behaviors and treatment outcomes. Accurate prognosis prediction for glioma patients is crucial for optimi...

Study of Attention-Guided CNN Framework for 3D MRI Glioma Segmentation and Grading Gliomas are the most deadly form of brain tumors in humans. Timely diagnosis of these tumors is a crucial step for effective tumor treatment. Magnetic Resonance Imaging (MRI) typically provides a non-invasive examination of brain lesions. However, manual inspection o...

Enabling Explainable Artificial Intelligence for Glioma Prognosis: Translational Insights from Transparent Machine Learning Academic Background This study is dedicated to developing a reliable technique to detect whether patients have a specific type of brain tumor—glioma—using various machine learning methods and deep learning methods, combined wi...

Survival Analysis of Glioblastoma Patients: An Overview Empowered by Data Engineering Introduction Glioblastoma is a type of tumor that occurs in glial cells and accounts for 26.7% of all primary brain and central nervous system tumors. Survival analysis of glioblastoma patients is a key task in clinical management due to the heterogeneity of the t...

Personalized Prediction of Glioma Growth Using Bayesian Inference Introduction Glioblastoma is the most aggressive type of primary brain tumor, characterized by highly invasive tumor cells that spread to surrounding tissues. Conventional medical imaging techniques cannot precisely identify these diffuse tumor boundaries, leading to suboptimal clini...

Study of Mathematical Models for Tumor Growth – Exploring Glioma Extension Using Longitudinal Magnetic Resonance Imaging A recent article published in the IEEE Transactions on Biomedical Engineering presents a systematic study on the mathematical modeling and growth patterns of gliomas (glioma). This research was conducted by Birkan Tunç, David A. ...

Research Report on the Regulation of Neuron-Glioma Interactions by CHD2 in Pediatric Gliomas Background High-grade gliomas (HGG) are fatal diseases in both adult and pediatric patients. Recent studies have shown that neuronal activity can promote the progression of various high-grade glioma subgroups. However, the epigenetic mechanisms regulating t...

Study of Neuroepithelial Genetic Markers and Prognosis in High-Grade Gliomas Background and Research Motivation High-grade gliomas are highly malignant brain tumors with generally poor patient prognosis. Previous preclinical model studies have suggested that interactions between neural and tumor cells drive tumor growth, but clinical validation of ...