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Hesham Elhalawani

Showing results (31-40 of 86) with videos related to

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Oncotarget|November 2, 2017
A large-scale retrospective study of the overall survival outcome in nasopharyngeal carcinoma with hypertension in Chinese populationPei Yang, Hesham Elhalawani, Yingrui Shi, et al.
Clinical and Translational Radiation Oncology|December 31, 2019
Stability analysis of CT radiomic features with respect to segmentation variation in oropharyngeal cancerRongjie Liu, Hesham Elhalawani, Abdallah Sherif Radwan Mohamed, et al.
Frontiers in Oncology|June 6, 2018
Exploring Applications of Radiomics in Magnetic Resonance Imaging of Head and Neck Cancer: A Systematic ReviewAmit Jethanandani, Timothy A Lin, Stefania Volpe, et al.
Chinese Clinical Oncology|February 11, 2020
Real-world applications of deep convolutional neural networks in diagnostic cancer imagingHesham Elhalawani, Pei Yang, Mohamed Abazeed, et al.
Scientific Reports|March 4, 2020
Clustering of Largely Right-Censored Oropharyngeal Head and Neck Cancer Patients for Discriminative Groupings to Improve Outcome PredictionJoel Tosado, Luka Zdilar, Hesham Elhalawani, et al.
American Journal of Cancer Research|May 5, 2017
Analysis of the correlation among hypertension, the intake of β-blockers, and overall survival outcome in patients undergoing chemoradiotherapy with inoperable stage III non-small cell lung cancerPei Yang, Weiye Deng, Yaqian Han, et al.
Journal of Neuro-Oncology|April 15, 2025
Impact of brain metastasis size at the time of radiotherapy on local control and radiation necrosisNarmeen S Rashid, Nayan Lamba, Paul J Catalano, et al.
Neuro-Oncology|June 1, 2023
A genomic score to predict local control among patients with brain metastases managed with radiationNayan Lamba, Daniel N Cagney, Paul J Catalano, et al.
Hematology/Oncology Clinics of North America|November 20, 2019
Imaging for Response Assessment in Radiation Oncology: Current and Emerging TechniquesSonja Stieb, Kendall Kiser, Lisanne van Dijk, et al.
Translational Cancer Research|February 4, 2022
A predictive model of radiation-related fibrosis based on the radiomic features of magnetic resonance imaging and computed tomographyJian Wang, Rongjie Liu, Yu Zhao, et al.
Pageof 9

Showing results (31-40 of 86) with videos related to

Sort By:
Pageof 9
Oncotarget|November 2, 2017
A large-scale retrospective study of the overall survival outcome in nasopharyngeal carcinoma with hypertension in Chinese populationPei Yang, Hesham Elhalawani, Yingrui Shi, et al.
Clinical and Translational Radiation Oncology|December 31, 2019
Stability analysis of CT radiomic features with respect to segmentation variation in oropharyngeal cancerRongjie Liu, Hesham Elhalawani, Abdallah Sherif Radwan Mohamed, et al.
Frontiers in Oncology|June 6, 2018
Exploring Applications of Radiomics in Magnetic Resonance Imaging of Head and Neck Cancer: A Systematic ReviewAmit Jethanandani, Timothy A Lin, Stefania Volpe, et al.
Chinese Clinical Oncology|February 11, 2020
Real-world applications of deep convolutional neural networks in diagnostic cancer imagingHesham Elhalawani, Pei Yang, Mohamed Abazeed, et al.
Scientific Reports|March 4, 2020
Clustering of Largely Right-Censored Oropharyngeal Head and Neck Cancer Patients for Discriminative Groupings to Improve Outcome PredictionJoel Tosado, Luka Zdilar, Hesham Elhalawani, et al.
American Journal of Cancer Research|May 5, 2017
Analysis of the correlation among hypertension, the intake of β-blockers, and overall survival outcome in patients undergoing chemoradiotherapy with inoperable stage III non-small cell lung cancerPei Yang, Weiye Deng, Yaqian Han, et al.
Journal of Neuro-Oncology|April 15, 2025
Impact of brain metastasis size at the time of radiotherapy on local control and radiation necrosisNarmeen S Rashid, Nayan Lamba, Paul J Catalano, et al.
Neuro-Oncology|June 1, 2023
A genomic score to predict local control among patients with brain metastases managed with radiationNayan Lamba, Daniel N Cagney, Paul J Catalano, et al.
Hematology/Oncology Clinics of North America|November 20, 2019
Imaging for Response Assessment in Radiation Oncology: Current and Emerging TechniquesSonja Stieb, Kendall Kiser, Lisanne van Dijk, et al.
Translational Cancer Research|February 4, 2022
A predictive model of radiation-related fibrosis based on the radiomic features of magnetic resonance imaging and computed tomographyJian Wang, Rongjie Liu, Yu Zhao, et al.
Pageof 9