101 citations · 327 across the 27 of their papers we have counts for
5 papers · 1 filter
Classification based deep learning models for lung cancer and disease using medical images
Ahmad Chaddad, Jihao Peng, Yihang Wu
The use of deep learning (DL) in medical image analysis has significantly improved the ability to predict lung cancer. In this study, we introduce a novel deep convolutional neural…
SHAP-Integrated Convolutional Diagnostic Networks for Feature-Selective Medical Analysis
Yan Hu, Ahmad Chaddad
This study introduces the SHAP-integrated convolutional diagnostic network (SICDN), an interpretable feature selection method designed for limited datasets, to address the challeng…
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…
Deep Radiomic Analysis for Predicting Coronavirus Disease 2019 in Computerized Tomography and X-ray Images
Ahmad Chaddad, Lama Hassan, Christian Desrosiers
This paper proposes to encode the distribution of features learned from a convolutional neural network using a Gaussian Mixture Model. These parametric features, called GMM-CNN, ar…
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…