MK
Mohammadhadi Khorrami
Emory University
Research areas: Medicine · Radiology, Nuclear Medicine and Imaging · Radiomics and Machine Learning in Medical Imaging · Lung Cancer Diagnosis and Treatment · Cancer Immunotherapy and Biomarkers
0000-0002-4141-8548
Employment
- 2014 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (21)
- Ten challenges and opportunities in computational immuno-oncology Save
- Radiomic predicts early response to CDK4/6 inhibitors in hormone receptor positive metastatic breast cancer Save
- A tumor vasculature–based imaging biomarker for predicting response and survival in patients with lung cancer treated with checkpoint inhibitors Save
- Novel Radiomic Measurements of Tumor-Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers Save
- Texture-based CT radiomics distinguishes radiation and immunotherapy induced pneumonitis in stage III NSCLC. Save
- Novel imaging biomarkers predict outcomes in stage III unresectable non-small cell lung cancer treated with chemoradiation and durvalumab Save
- Novel Non-Invasive Radiomic Signature on CT Scans Predicts Response to Platinum-Based Chemotherapy and Is Prognostic of Overall Survival in Small Cell Lung Cancer Save
- Distinguishing granulomas from adenocarcinomas by integrating stable and discriminating radiomic features on non-contrast computed tomography scans. Save
- Novel, non-invasive imaging approach to identify patients with advanced non-small cell lung cancer at risk of hyperprogressive disease with immune checkpoint blockade Save
- Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study Save
- Changes in CT radiomic features associated with lymphocyte distribution predict overall survival and response to immunotherapy in non-small cell lung cancer Save
- P2.04-16 Novel CT Based Radiomic Features are Prognostic and Predictive of Benefit of Chemoimmunotherapy in Advanced Non-Squamous NSCLC Save
- Predicting pathologic response to neoadjuvant chemoradiation in resectable stage III non-small cell lung cancer patients using computed tomography radiomic features Save
- A combination of intra- and peritumoral features on baseline CT scans is associated with overall survival in non-small cell lung cancer patients treated with immune checkpoint inhibitors: a multi-agent multi-site study Save
- Combination of Peri- and Intratumoral Radiomic Features on Baseline CT Scans Predicts Response to Chemotherapy in Lung Adenocarcinoma Save
- Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas Save
- Corrigendum to “Predicting pathologic response to neoadjuvant chemoradiation in resectable stage III non-small cell lung cancer patients using computed tomography radiomic features” [Lung Cancer 135 (September) (2019) 1–9](S0169500219305136)(10.1016/j.lu… Save
- P2.04-17 Pre-Therapy Radiomic Features Can Distinguish Hyperprogression from Other Response Patterns to PD1/PD-L1 Inhibitors in NSCLC Save
- Combination of CT derived radiomic features and lymphovascular invasion status to predict disease recurrence following trimodality therapy in non-small cell lung cancer. Save
- Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography Save