A
Ali Sabri
Researcher at McMaster University
Publications - 15
Citations - 307
Ali Sabri is an academic researcher from McMaster University. The author has contributed to research in topics: Computer science & Convolutional neural network. The author has an hindex of 7, co-authored 14 publications receiving 177 citations. Previous affiliations of Ali Sabri include Jewish General Hospital & Dalhousie University.
Papers
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Journal ArticleDOI
Radiologic management of COVID-19: Preliminary experience of the iranian society of radiology COVID-19 consultant group (ISRCC)
Arash Mahdavi,Nastaran Khalili,Amir H. Davarpanah,Taraneh Faghihi,Ali Mahdavi,Sara Haseli,Ali Sabri,Shahram Kahkouee,Mohammad Ali Kazemi,Payam Mehrian,Farahnaz Falahati,Mehrdad Bakhshayeshkaram,Morteza Sanei Taheri +12 more
Journal ArticleDOI
Novel Screening and Triage Strategy in Iran During Deadly Coronavirus Disease 2019 (COVID-19) Epidemic: Value of Humanitarian Teleconsultation Service.
Amir H. Davarpanah,Arash Mahdavi,Ali Sabri,Taraneh Faghihi Langroudi,Shahram Kahkouee,Sara Haseli,Mohammad Ali Kazemi,Payam Mehrian,Ali Mahdavi,Farahnaz Falahati,Abuzar Moradi Tuchayi,Mehrdad Bakhshayeshkaram,Morteza Sanei Taheri +12 more
Posted Content
COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse Learning.
TL;DR: In this paper, the authors introduced COVID-Net CT-2, a neural network tailored for detection of COVID19 cases from chest CT images as part of the open source COVIDNet initiative.
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Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer.
Jay Kumar Raghavan Nair,Jay Kumar Raghavan Nair,Jay Kumar Raghavan Nair,Umar Abid Saeed,Umar Abid Saeed,Connor C. McDougall,Ali Sabri,Ali Sabri,Bojan Kovacina,B V S Raidu,Riaz Ahmed Khokhar,Stephan Probst,Vera Hirsh,Jeffrey Chankowsky,Léon C van Kempen,Léon C van Kempen,Jana Taylor +16 more
TL;DR: Non-small cell lung cancer texture analysis using FGD-PET and CT images can identify tumors with mutations in EGFR and could be valuable for pretreatment assessment and prognosis in precision therapy.
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Predicting EGFR mutation status in lung cancer:Proposal for a scoring model using imaging and demographic characteristics.
TL;DR: A weighted scoring system combining imaging and demographic data holds promise as a predictor of EGFR status and may help determine which patients would benefit from molecular profiling and help inform treatment decisions when molecular profiling is not possible.