The natural history and treatment landscape of primary brain tumours are complicated by the
varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low …

Glioma represents a dominant primary intracranial malignancy in the central nervous
system. Artificial intelligence that mainly includes machine learning, and deep learning …

Although machine learning (ML) has shown promise across disciplines, out-of-sample
generalizability is concerning. This is currently addressed by sharing multi-site data, but …

Gliomas can be classified into five molecular groups based on the status of IDH mutation,
1p/19q codeletion, and TERT promoter mutation, whereas they need to be obtained by …

(1) Background: Transfer learning refers to machine learning techniques that focus on
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …

With the continuous development of medical image informatics technology, more and more
high-throughput quantitative data could be extracted from digital medical images, which has …

Despite the remarkable advances in cancer diagnosis, treatment, and management over the
past decade, malignant tumors remain a major public health problem. Further progress in …

AI is a broad concept, grouping initiatives that use a computer to perform tasks that would
usually require a human to complete. AI methods are well suited to predict clinical outcomes …

Recent developments in glioma categorization based on biological genotypes and
application of computational machine learning or deep learning based predictive models …

Survival analysis is a critical task in glioma patient management due to the inter and intra
tumor heterogeneity. In clinical practice, clinicians estimate the survival with their …