Machine learning prediction of glioblastoma patient one-year survival

Glioblastoma (GBM) is a grade IV astrocytoma formed primarily from cancerous astrocytes and sustained by intense angiogenesis. GBM often causes non-specific symptoms, creating difficulty for diagnosis. This study aimed to utilize machine learning techniques to provide an accurate one-year survival prognosis for GBM patients using clinical and genomic data from the Chinese Glioma Genome Atlas. Logistic regression (LR), support vector machines (SVM), random forest (RF), and ensemble models were used to identify and select predictors for GBM survival and to classify patients into those with an overall survival (OS) of less than one year and one year or greater. With regards to overall survival, a significant (p \u3c 0.05, n = 175) correlation was found with age (negative), radiation treatment (positive), and chemotherapy treatment (positive). IDH1 mutation and 1p19q codeletion showed insignificant correlation with OS in this dataset. This potentially implies that IDH1 mutation alone, although important in secondary GBM prognosis, is insignificant for primary GBM prognosis. 1p19q codeletion also appeared to be insignificant for primary GBM prognosis when considered alone. The ensemble model had the highest overall accuracy, achieving a mean AUC score of 0.644 and an F1 score of 0.799

Profiting from growth: Trade, investment and the ASEAN-China technology gap

While outward FDI inflows have increased since 2008, the volume of Southeast Asia’s exports to China has slowed down, prompting discussion about whether this will affect Southeast Asia’s growth. This article empirically tests China’s impact on Southeast Asia’s growth using a nonlinear framework, and finds that economic linkages between Southeast Asia and China have been changing since the mid-1990s, especially during the 1997 and 2008 financial crises and the 2012 bilateral diplomatic change; that FDI is more important to economic growth than exports across Southeast Asia; and that there is no industrial technology gap between Southeast Asia and China