Reza Iranzad
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Also affiliated: Sharif University of Technology (2021); FedEx (United States) (2024)
Formerly Arkansas Affiliated with University of Arkansas through 2024.
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Reza Iranzad's research focuses on the application of statistical learning and image processing techniques to medical data. He has explored gradient boosted trees and other tree-based ensemble methods for analyzing spatial data, including their use in medical imaging. Iranzad has investigated the prediction of survival outcomes for non-small cell lung cancer patients using multitask learning radiomics on longitudinal imaging data. His work also includes the development of structured adaptive boosting trees for detecting multicellular aggregates in fluorescence intravital microscopy, specifically studying neutrophils and blood platelets in animal models. Iranzad also has experience in developing operational models for healthcare settings, such as a model for operating room scheduling. His scholarly metrics include an h-index of 4, with 7 total publications and 290 citations.
Metrics
- h-index: 4
- Publications: 7
- Citations: 290
Selected Publications
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Structured adaptive boosting trees for detection of multicellular aggregates in fluorescence intravital microscopy (2024)
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Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer (2022)
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Gradient boosted trees for spatial data and its application to medical imaging data (2021)
Collaboration Network
Top Collaborators
- Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
- Gradient boosted trees for spatial data and its application to medical imaging data
- Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
- Gradient boosted trees for spatial data and its application to medical imaging data
- Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
- Gradient boosted trees for spatial data and its application to medical imaging data
- Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
- Gradient boosted trees for spatial data and its application to medical imaging data
- Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
- Gradient boosted trees for spatial data and its application to medical imaging data
- Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
- Gradient boosted trees for spatial data and its application to medical imaging data
- Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
- Gradient boosted trees for spatial data and its application to medical imaging data
- Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
- Gradient boosted trees for spatial data and its application to medical imaging data
- Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
- Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
- Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
- Gradient boosted trees for spatial data and its application to medical imaging data
- Structured adaptive boosting trees for detection of multicellular aggregates in fluorescence intravital microscopy
- Structured adaptive boosting trees for detection of multicellular aggregates in fluorescence intravital microscopy
- Structured adaptive boosting trees for detection of multicellular aggregates in fluorescence intravital microscopy
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