Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered
data with nuanced decision making. Cancer offers a unique context for medical decisions …

Deep learning is a branch of artificial intelligence where networks of simple interconnected
units are used to extract patterns from data in order to solve complex problems. Deep …

Radiomics is a relatively new word for the field of radiology, meaning the extraction of a high
number of quantitative features from medical images. Artificial intelligence (AI) is broadly a …

Purpose: Isocitrate dehydrogenase (IDH) mutations in glioma patients confer longer survival
and may guide treatment decision making. We aimed to predict the IDH status of gliomas …

Recent advancements in signal processing (SP) and machine learning, coupled with
electronic medical record kee** in hospitals and the availability of extensive sets of …

Background: Accurate glioma grading before surgery is of the utmost importance in
treatment planning and prognosis prediction. But previous studies on magnetic resonance …

Purpose The aim of this systematic review was to analyse literature on artificial intelligence
(AI) and radiomics, including all medical imaging modalities, for oncological and non …

This article is a comprehensive review of the basic background, technique, and clinical
applications of artificial intelligence (AI) and radiomics in the field of neuro-oncology. A …

This work delivers a novel technique to detect brain tumor with the help of enhanced
watershed modeling integrated with a modified ResNet50 architecture. It also involves …

Due to the exponential growth of computational algorithms, artificial intelligence (AI)
methods are poised to improve the precision of diagnostic and therapeutic methods in …