3 papers
eess.IV2025
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification
Mohaddeseh Chegini, Ali Mahloojifar
The Computer_Aided Diagnosis (CAD) systems facilitate accurate diagnosis of diseases. The development of CADs by leveraging third generation neural network, namely, Spiking Neural…
cs.CV2025
BI-RADS prediction of mammographic masses using uncertainty information extracted from a Bayesian Deep Learning model
Mohaddeseh Chegini, Ali Mahloojifar
The BI_RADS score is a probabilistic reporting tool used by radiologists to express the level of uncertainty in predicting breast cancer based on some morphological features in mam…
cs.CV2024
Reliable Breast Cancer Molecular Subtype Prediction based on uncertainty-aware Bayesian Deep Learning by Mammography
Mohaddeseh Chegini, Ali Mahloojifar
Breast cancer is a heterogeneous disease with different molecular subtypes, clinical behavior, treatment responses as well as survival outcomes. The development of a reliable, accu…