More information: Faris Rustom et al, Deep Learning and Transfer Learning for Brain Tumor Detection and Classification, Biology Methods and Protocols (2024). DOI: 10.1093/biomethods/bpae080 ...

While the best-performing proposed model was about 6% less accurate than standard human detection, the research successfully showed the quantitative improvement brought on by the training model.

In a major breakthrough, a team of researchers from The City College of New York and Memorial Sloan Kettering Cancer Center ...

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 ...

A deep learning model trained on fundus photographs showed promise in the detection of severe glaucoma, with lower accuracy ...

The project will bring in 29 institutions from North America, Europe and India and will use privacy-preserved data to train AI models. Federated learning has been described as being born at the ...

The researchers set out to create a deep learning model that can accurately estimate patient-specific tumor progression using the Proliferation-Invasion (PI) model, a mathematical model often used ...

More information: Cameron Meaney et al, Deep learning characterization of brain tumours with diffusion weighted imaging, Journal of Theoretical Biology (2022). DOI: 10.1016/j.jtbi.2022.111342 ...