Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year
survival rate of high-grade glioma is poor. Magnetic resonance imaging (MRI) is essential for …

Since its discovery in the early 1990s, functional MRI (fMRI) has been used to study human
brain function. One well-established application of fMRI in the clinical setting is the …

Gliomas are the most common primary brain malignancies. Accurate and robust tumor
segmentation and prediction of patients' overall survival are important for diagnosis …

Glioblastoma (GBM) is the most common and deadly malignant brain tumor. For
personalized treatment, an accurate pre-operative prognosis for GBM patients is highly …

Brain functional network has been increasingly used in understanding brain functions and
diseases. While many network construction methods have been proposed, the progress in …

Background Machine learning (ML) algorithms are increasingly explored in glioma
prognostication. Random survival forest (RSF) is a common ML approach in analyzing time …

Introduction High-grade gliomas cause cognitive impairment in those who suffer from them.
However, there is a lack of precise data describing the cognitive deficit that occurs in this …

Early and accurate prediction of overall survival (OS) time can help to obtain better treatment
planning for brain tumor patients. Although many OS time prediction methods have been …

Distinguishing bipolar depression (BD) from unipolar depression (UD) based on symptoms
only is challenging. Brain functional connectivity (FC), especially dynamic FC, has emerged …

Gliomas are neurologically devastating tumors with generally poor outcomes. Traditionally,
survival prediction in glioma is studied from clinical features using statistical approaches …