Deep learning model predicts how individual cells influence disease outcomes

A computational method called scSurv, developed by researchers at Institute of Science Tokyo, links individual cells to patient outcomes using widely available bulk RNA sequencing data. The approach ...
IEEE

Segmentation Variability in Bayesian U-Net versus Manual Annotations: Impact on Radiomic Reproducibility in Lung Tumor CT Images

Abstract: Radiomic analysis is highly sensitive to variations in Region of Interest (ROI) segmentation. Automatic segmentation methods based on Deep Learning (DL) can enhance radiomic reproducibility ...
IEEE

Spiking Neural Network for Visual Attention in Brain Tumor Segmentation

Abstract: Spiking Neural Networks (SNNs) with visual attention mechanisms offer a biologically-inspired approach for medical image analysis and segmentation, aiming to address the high computational ...