This work evaluates two advanced deep learning architecture: Convolutional Neural Network (CNN),VGG-16 model, EfficientNetB3 algorithm. Both are trained and tested using a dataset from the National ...

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, ...

Researchers at Duke University Medical Center have developed a deep-learning-based computer-aided detection (CAD) system to identify difficult-to-detect brain metastases on MR images. The algorithm ...

University of Waterloo. (2023, January 16). Using machine learning to predict brain tumor progression. ScienceDaily. Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2023 / 01 ...

The University of Pennsylvania Perelman School of Medicine joined with Intel Labs to conduct a research study to improve brain tumor detection by using a kind of machine learning called Federated ML.

Worldwide, brain and central nervous system cancers accounted for over 321,000 new cases and 248,500 deaths in 2022, according to a Global Cancer Observatory report by the World Health ...

Their deep learning system, called Sturgeon, was first tested on frozen tumor samples from previous brain cancer operations. It accurately diagnosed 45 of 50 cases within 40 minutes of starting ...