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Khadijeh Saednia

Showing results (1-10 of 10) with videos related to

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|September 10, 2022
A Cascaded Deep Learning Framework for Segmentation of Nuclei in Digital Histology ImagesKhadijeh Saednia, William T Tran, Ali Sadeghi-Naini
Medical Physics|July 5, 2023
A hierarchical self-attention-guided deep learning framework to predict breast cancer response to chemotherapy using pre-treatment tumor biopsiesKhadijeh Saednia, William T Tran, Ali Sadeghi-Naini
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 6, 2020
An Attention-Guided Deep Neural Network for Annotating Abnormalities in Chest X-ray Images: Visualization of Network Decision Basis<sup>.</sup>Khadijeh Saednia, Ali Jalalifar, Shahin Ebrahimi, et al.
Computers in Biology and Medicine|July 14, 2020
Multi-scale segmentation in GBM treatment using diffusion tensor imagingRoushanak Rahmat, Khadijeh Saednia, Mohammad Reza Haji Hosseini Khani, et al.
International Journal of Radiation Oncology, Biology, Physics|January 27, 2020
Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine LearningKhadijeh Saednia, Sami Tabbarah, Andrew Lagree, et al.
Scientific Reports|April 14, 2021
A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networksAndrew Lagree, Majidreza Mohebpour, Nicholas Meti, et al.
Journal of Medical Imaging and Radiation Sciences|August 27, 2019
Personalized Breast Cancer Treatments Using Artificial Intelligence in Radiomics and PathomicsWilliam T Tran, Katarzyna Jerzak, Fang-I Lu, et al.
Scientific Reports|June 11, 2022
Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsiesKhadijeh Saednia, Andrew Lagree, Marie A Alera, et al.
JCO Clinical Cancer Informatics|January 13, 2021
Machine Learning Frameworks to Predict Neoadjuvant Chemotherapy Response in Breast Cancer Using Clinical and Pathological FeaturesNicholas Meti, Khadijeh Saednia, Andrew Lagree, et al.
Genes|September 28, 2023
Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine LearningAudrey Shiner, Alex Kiss, Khadijeh Saednia, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|September 10, 2022
A Cascaded Deep Learning Framework for Segmentation of Nuclei in Digital Histology ImagesKhadijeh Saednia, William T Tran, Ali Sadeghi-Naini
Medical Physics|July 5, 2023
A hierarchical self-attention-guided deep learning framework to predict breast cancer response to chemotherapy using pre-treatment tumor biopsiesKhadijeh Saednia, William T Tran, Ali Sadeghi-Naini
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 6, 2020
An Attention-Guided Deep Neural Network for Annotating Abnormalities in Chest X-ray Images: Visualization of Network Decision Basis<sup>.</sup>Khadijeh Saednia, Ali Jalalifar, Shahin Ebrahimi, et al.
Computers in Biology and Medicine|July 14, 2020
Multi-scale segmentation in GBM treatment using diffusion tensor imagingRoushanak Rahmat, Khadijeh Saednia, Mohammad Reza Haji Hosseini Khani, et al.
International Journal of Radiation Oncology, Biology, Physics|January 27, 2020
Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine LearningKhadijeh Saednia, Sami Tabbarah, Andrew Lagree, et al.
Scientific Reports|April 14, 2021
A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networksAndrew Lagree, Majidreza Mohebpour, Nicholas Meti, et al.
Journal of Medical Imaging and Radiation Sciences|August 27, 2019
Personalized Breast Cancer Treatments Using Artificial Intelligence in Radiomics and PathomicsWilliam T Tran, Katarzyna Jerzak, Fang-I Lu, et al.
Scientific Reports|June 11, 2022
Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsiesKhadijeh Saednia, Andrew Lagree, Marie A Alera, et al.
JCO Clinical Cancer Informatics|January 13, 2021
Machine Learning Frameworks to Predict Neoadjuvant Chemotherapy Response in Breast Cancer Using Clinical and Pathological FeaturesNicholas Meti, Khadijeh Saednia, Andrew Lagree, et al.
Genes|September 28, 2023
Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine LearningAudrey Shiner, Alex Kiss, Khadijeh Saednia, et al.
Pageof 1