This study proposes a hybrid detection architecture to determine the presence of brain tumors. The system incorporates five different deep convolutional neural networks (CNNs) for feature extraction, ...

In response, advanced techniques leveraging deep learning neural networks have emerged as promising solutions for automated and accurate brain tumor detection ... network (CNN) architecture, and the ...

Here we present a deep learning-based framework for brain tumor segmentation and survival prediction in glioma, using multimodal MRI scans ... Cascaded framework and architecture of CA-CNN. The second ...

(Courtesy: Devon Godfrey, Duke University) Researchers at Duke University Medical Center have developed a deep-learning-based computer-aided detection (CAD) system to ... patients with 563 brain ...

Researchers have created a computational model to predict the growth of deadly brain ... They're using machine learning to fully analyze a patient's tumour, to better predict cancer progression.

New machine learning (ML)-based tool developed by researchers helps detect cancer-causing tumors in the brain and spinal cord. ‘aGBMDriver' (GlioBlastoma Mutiforme Drivers), the machine learning ...

Now scientists in the Netherlands report using artificial ... Their deep learning system, called Sturgeon, was first tested on frozen tumor samples from previous brain cancer operations.