arXiv Machine Learning By Hiram Zuniga, Ulises Orozco-Rosas, Kenia Picos

A comparison of CNN architectures for Alzheimer's disease detection in single-view MRI scans

Read the original on arXiv Machine Learning →

arXiv:2608. 11762v1 Announce Type: cross Abstract: Alzheimer's disease is a leading cause of death with no cure.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

Hugging Face Trending Papers
Jun 27

A Deep Multiscale Neural Network for Accurate Neurological Disorder Detection from MRI Scans and Real-Time Web Deployment

Neurological disorders involve diverse pathologies of the brain and nervous system, making early and accurate detection essential. While many deep CNNs have been developed for MRI-based classification of neurological disorders, most are optimized for binary tasks and often fail to capture the multi-class features needed to distinguish subtle anatomical differences across conditions.

Hugging Face Trending Papers
Jun 21

Multi-cancer detection using a computationally efficient CNN with transfer learning

This study introduces a computationally efficient convolutional neural network (CNN) architecture enhanced with transfer learning for multi-cancer detection using biomedical images. The proposed lightweight CNN model is designed to reduce computational complexity while maintaining high classification performance, making it suitable for deployment in resource-constrained environments.