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Chiharu Sako

Showing results (11-20 of 26) with videos related to

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Neurosurgical Focus|August 8, 2023
Radiomic signatures of meningiomas using the Ki-67 proliferation index as a prognostic marker of clinical outcomesOmaditya Khanna, Anahita Fathi Kazerooni, Sherjeel Arif, et al.
Neurosurgery|August 30, 2021
Machine Learning Using Multiparametric Magnetic Resonance Imaging Radiomic Feature Analysis to Predict Ki-67 in World Health Organization Grade I MeningiomasOmaditya Khanna, Anahita Fathi Kazerooni, Christopher J Farrell, et al.
Scientific Reports|February 28, 2024
Integrating imaging and genomic data for the discovery of distinct glioblastoma subtypes: a joint learning approachJun Guo, Anahita Fathi Kazerooni, Erik Toorens, et al.
Neuro-Oncology Advances|February 1, 2021
Multi-institutional noninvasive in vivo characterization of <i>IDH</i>, 1p/19q, and EGFRvIII in glioma using neuro-Cancer Imaging Phenomics Toolkit (neuro-CaPTk)Saima Rathore, Suyash Mohan, Spyridon Bakas, et al.
Scientific Reports|May 24, 2022
Clinical measures, radiomics, and genomics offer synergistic value in AI-based prediction of overall survival in patients with glioblastomaAnahita Fathi Kazerooni, Sanjay Saxena, Erik Toorens, et al.
Neuroimage|July 1, 2020
Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic trainingSiddhesh Thakur, Jimit Doshi, Sarthak Pati, et al.
JCO Clinical Cancer Informatics|March 20, 2020
Cancer Imaging Phenomics via CaPTk: Multi-Institutional Prediction of Progression-Free Survival and Pattern of Recurrence in GlioblastomaAnahita Fathi Kazerooni, Hamed Akbari, Gaurav Shukla, et al.
Communications Medicine|March 2, 2025
The radiogenomic and spatiogenomic landscapes of glioblastoma and their relationship to oncogenic driversAnahita Fathi Kazerooni, Hamed Akbari, Xiaoju Hu, et al.
JAMA Network Open|January 28, 2026
Deep-Learning Serial CT Prediction of Survival in Immunotherapy-Treated Non-Small Cell Lung CancerChiharu Sako, Brenda F Kurland, Taly G Schmidt, et al.
Journal of Medical Imaging (Bellingham, Wash.)|September 2, 2024
Predicting peritumoral glioblastoma infiltration and subsequent recurrence using deep-learning-based analysis of multi-parametric magnetic resonance imagingSunwoo Kwak, Hamed Akbari, Jose A Garcia, et al.
Pageof 3

Showing results (11-20 of 26) with videos related to

Sort By:
Pageof 3
Neurosurgical Focus|August 8, 2023
Radiomic signatures of meningiomas using the Ki-67 proliferation index as a prognostic marker of clinical outcomesOmaditya Khanna, Anahita Fathi Kazerooni, Sherjeel Arif, et al.
Neurosurgery|August 30, 2021
Machine Learning Using Multiparametric Magnetic Resonance Imaging Radiomic Feature Analysis to Predict Ki-67 in World Health Organization Grade I MeningiomasOmaditya Khanna, Anahita Fathi Kazerooni, Christopher J Farrell, et al.
Scientific Reports|February 28, 2024
Integrating imaging and genomic data for the discovery of distinct glioblastoma subtypes: a joint learning approachJun Guo, Anahita Fathi Kazerooni, Erik Toorens, et al.
Neuro-Oncology Advances|February 1, 2021
Multi-institutional noninvasive in vivo characterization of <i>IDH</i>, 1p/19q, and EGFRvIII in glioma using neuro-Cancer Imaging Phenomics Toolkit (neuro-CaPTk)Saima Rathore, Suyash Mohan, Spyridon Bakas, et al.
Scientific Reports|May 24, 2022
Clinical measures, radiomics, and genomics offer synergistic value in AI-based prediction of overall survival in patients with glioblastomaAnahita Fathi Kazerooni, Sanjay Saxena, Erik Toorens, et al.
Neuroimage|July 1, 2020
Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic trainingSiddhesh Thakur, Jimit Doshi, Sarthak Pati, et al.
JCO Clinical Cancer Informatics|March 20, 2020
Cancer Imaging Phenomics via CaPTk: Multi-Institutional Prediction of Progression-Free Survival and Pattern of Recurrence in GlioblastomaAnahita Fathi Kazerooni, Hamed Akbari, Gaurav Shukla, et al.
Communications Medicine|March 2, 2025
The radiogenomic and spatiogenomic landscapes of glioblastoma and their relationship to oncogenic driversAnahita Fathi Kazerooni, Hamed Akbari, Xiaoju Hu, et al.
JAMA Network Open|January 28, 2026
Deep-Learning Serial CT Prediction of Survival in Immunotherapy-Treated Non-Small Cell Lung CancerChiharu Sako, Brenda F Kurland, Taly G Schmidt, et al.
Journal of Medical Imaging (Bellingham, Wash.)|September 2, 2024
Predicting peritumoral glioblastoma infiltration and subsequent recurrence using deep-learning-based analysis of multi-parametric magnetic resonance imagingSunwoo Kwak, Hamed Akbari, Jose A Garcia, et al.
Pageof 3