no code implementations • 17 Nov 2022 • Ahmad Chaddad, Qizong Lu, Jiali Li, Yousef Katib, Reem Kateb, Camel Tanougast, Ahmed Bouridane, Ahmed Abdulkadir
(2) Domain adaptation and transfer learning enable AI models to be trained and applied across multiple domains.
no code implementations • 8 Aug 2022 • Longzhao Huang, Yujie Li, Xu Wang, Haoyu Wang, Ahmed Bouridane, Ahmad Chaddad
We propose a differential residual model (DRNet) combined with a new loss function to make use of the difference information of two eye images.
no code implementations • 9 Jun 2022 • Ahmad Chaddad, Paul Daniel Mingli Zhang, Saima Rathore, Paul Sargos, Christian Desrosiers, Tamim Niazi
These results demonstrate the usefulness of proposed DRFs as non-invasive biomarker for predicting treatment response in patients with brain tumors.
no code implementations • 5 Jun 2022 • Ahmad Chaddad, Jiali Li, Qizong Lu, Yujie Li, Idowu Paul Okuwobi, Camel Tanougast, Christian Desrosiers, Tamim Niazi
With AI, new radiomic models using the deep learning techniques will be also described.
no code implementations • 4 Jun 2022 • Ahmad Chaddad, Lama Hassan, Christian Desrosiers
Our results suggest that the proposed GMM-CNN features could improve the prediction of COVID-19 in chest computed tomography and X-ray scans.
no code implementations • 4 Jun 2022 • Ahmad Chaddad, Mingli Zhang, Lama Hassan, Tamim Niazi
Combined the immune markers with DRFs and clinical variables, Kaplan-Meier estimator and Log-rank test achieved the most significant difference between predicted groups of patients (short-term versus long-term survival) with p\,=\, 4. 31$\times$10$^{-7}$ compared to p\,=\, 0. 03 for Immune cell markers, p\,=\, 0. 07 for clinical variables , and p\,=\, 1. 45$\times$10$^{-5}$ for DRFs.
no code implementations • 4 Jun 2022 • Ahmad Chaddad, Yousef Katib, Lama Hassan
Purpose of review: Artificial intelligence (AI) has become popular in medical applications, specifically as a clinical support tool for computer-aided diagnosis.
no code implementations • 15 Nov 2019 • Ahmad Chaddad, Saima Rathore, Mingli Zhang, Christian Desrosiers, Tamim Niazi
This paper proposes to use deep radiomic features (DRFs) from a convolutional neural network (CNN) to model fine-grained texture signatures in the radiomic analysis of recurrent glioblastoma (rGBM).
no code implementations • 29 Nov 2017 • Ahmad Chaddad, Behnaz Naisiri, Marco Pedersoli, Eric Granger, Christian Desrosiers, Matthew Toews
This paper proposes a principled information theoretic analysis of classification for deep neural network structures, e. g. convolutional neural networks (CNN).