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Azadeh Tabari

As seen in: MDPI, medRxiv, Academic Radiology
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Articles

MRI-based Radiomics for Predicting Prostate Cancer Grade Groups: A Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies

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By Nima Broomand Lomer, Houman Sotoudeh, Azadeh Tabari, Drew Torigian, Mohammad Amin Ashoobi, Amir Mahmoud Ahmadzadeh
| Academic Radiology Verified
Key Words Radiomics Prostate cancer Gleason Grade group Artificial intelligence Machine learning Get full text access Log in, subscribe or purchase for full access. References 1. Rawla, P. Epidemiology of prostate cancer World J Oncol. 2019; 10:63-89 2. Siegel, R.L. ∙ Miller, K.D. ∙ Wagle, N.S. ... Cancer statistics, 2023 CA Cancer J Clin. 2023; 73:17-48 3. Whiting, D. ∙ Bott, S.R.J. Current diagnostics for prostate cancer Prostate cancer Exon Publications, Brisbane (AU), 2021 4.
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An artificial-intelligence interpretable tool to predict risk of deep vein thrombosis after endovenous thermal ablation

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By Yu Ma, Azadeh Tabari, Anthony Gebran, Haytham M Kaafarani
| medRxiv
The authors have declared no competing interest. This study did not receive any funding I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethical standards were upheld throughout the study and approved by the institutional review board of Massachusetts General Hospital.
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From Machine Learning to Patient Outcomes: A Comprehensive Review of AI in Pancreatic Cancer

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By Satvik Tripathi, Azadeh Tabari, Arian Mansur, Harika Dabbara
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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