167 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Iran University of Medical SciencesIR6 papers
- University of British ColumbiaCA5 papers
- Kerman University of Medical SciencesIR4 papers
- University Hospital of GenevaCH4 papers
- University of GenevaCH4 papers
- University Medical Center GroningenNL3 papers
- University of GroningenNL3 papers
- University of Southern DenmarkDK3 papers
- Deakin UniversityAU2 papers
- InsermFR2 papers
- Johns Hopkins UniversityUS2 papers
- Shahid Beheshti UniversityIR2 papers
8 papers
FCM-DNN: diagnosing coronary artery disease by deep accuracy Fuzzy C-Means clustering model
Javad Hassannataj Joloudari, Hamid Saadatfar, Mohammad GhasemiGol +6
Cardiovascular disease is one of the most challenging diseases in middle-aged and older people, which causes high mortality. Coronary artery disease (CAD) is known as a common card…
Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari +12
Coronavirus, or COVID-19, is a hazardous disease that has endangered the health of many people around the world by directly affecting the lungs. COVID-19 is a medium-sized, coated…
Non-Invasive Fuhrman Grading of Clear Cell Renal Cell Carcinoma Using Computed Tomography Radiomics Features and Machine Learning
Mostafa Nazari, Isaac Shiri, Ghasem Hajianfar +4
Purpose: To identify optimal classification methods for computed tomography (CT) radiomics-based preoperative prediction of clear cells renal cell carcinoma (ccRCC) grade. Methods…
Cardiac SPECT Radiomics Features Repeatability and Reproducibility: A Multi Scanner Phantom Study
Mohammad Edalat-Javid, Isaac Shiri, Ghasem Hajianfar +7
Background: The aim of this study was to assess the robustness of cardiac SPECT radiomics features against changes in imaging settings including acquisition and reconstruction sett…
Non-Invasive MGMT Status Prediction in GBM Cancer Using Magnetic Resonance Images (MRI) Radiomics Features: Univariate and Multivariate Machine Learning Radiogenomics Analysis
Ghasem Hajianfar, Isaac Shiri, Hassan Maleki +4
Background and aim: This study aimed to predict methylation status of the O-6 methyl guanine-DNA methyl transferase (MGMT) gene promoter status by using MRI radiomics features, as…
Next Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Approaches
Isaac Shiri, Hassan Maleki, Ghasem Hajianfar +5
Aim: In the present work, we aimed to evaluate a comprehensive radiomics framework that enabled prediction of EGFR and KRAS mutation status in NSCLC cancer patients based on PET an…
PET/CT Radiomic Sequencer for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients
Isaac Shiri, Hassan Maleki, Ghasem Hajianfar +5
The aim of this study was to develop radiomic models using PET/CT radiomic features with different machine learning approaches for finding best predictive epidermal growth factor r…
Optimal Relay Location in Diffusion Based Molecular Communications
Ghazaleh Ardeshiri, Ali Jamshidi, Alireza Keshavarz-Haddad
Molecular Communications via Diffusion (MCvD) is a promising paradigm which enables nano-machines to communicate with each other. However, the reliability of existing systems degra…