39 citations · 67 across the 4 of their papers we have counts for
4 papers
Deep radiomic signature with immune cell markers predicts the survival of glioma patients
Ahmad Chaddad, Paul Daniel Mingli Zhang, Saima Rathore +3
Imaging biomarkers offer a non-invasive way to predict the response of immunotherapy prior to treatment. In this work, we propose a novel type of deep radiomic features (DRFs) comp…
Can autism be diagnosed with AI?
Ahmad Chaddad, Jiali li, Qizong Lu +5
Radiomics with deep learning models have become popular in computer-aided diagnosis and have outperformed human experts on many clinical tasks. Specifically, radiomic models based…
Modeling of Textures to Predict Immune Cell Status and Survival of Brain Tumour Patients
Ahmad Chaddad, Mingli Zhang, Lama Hassan +1
Radiomics has shown a capability for different types of cancers such as glioma to predict the clinical outcome. It can have a non-invasive means of evaluating the immunotherapy res…
Deep radiomic features from MRI scans predict survival outcome of recurrent glioblastoma
Ahmad Chaddad, Saima Rathore, Mingli Zhang +2
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 gl…