Nathaniel Braman
Picture Health, Tempus Labs Inc, Case Western Reserve University, Vanderbilt University, IBM Research - Almaden
Research areas: Medicine · Radiology, Nuclear Medicine and Imaging · Radiomics and Machine Learning in Medical Imaging · MRI in cancer diagnosis · AI in cancer detection
0000-0001-5603-0821
About
Nathaniel Braman is Co-Founder and VP of AI Research & Development at Picture Health, where he leads the development and real-world deployment of AI imaging biomarkers at the intersection of radiology, oncology, and drug development. His work spans automated imaging readouts and radiomic endpoints for clinical trials, and the design of interpretable, biologically-grounded radiology biomarkers — including the QVT Score, a quantitative vascular tortuosity biomarker derived from routine CT for non-small cell lung cancer. He holds a Ph.D. in Biomedical Engineering from Case Western Reserve University, where he trained in the Madabhushi lab, and previously worked in radiology AI and precision oncology at Tempus and IBM Research.
Employment
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Picture Health Co-Founder2021 - Present
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Picture Health Vice President, AI Research & Development2021 - Present
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Tempus Labs Inc Machine Learning Scientist2020 - 2021
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IBM Research - Almaden Research Intern2018 - 2019
Education
- 2015 - 2020
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Vanderbilt University B.Eng.2011 - 2015
Projects & Funding
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Radiogenomic tools for prediction of breast cancer neo-adjuvant chemotherapy response from pre-treatment MRI National Cancer Institute2018 - 2021
Publications (30)
- QVT score, a radiomic biomarker of vascular complexity, enables prognostication and monitoring of NSCLC immunotherapy Save
- Radiomic predicts early response to CDK4/6 inhibitors in hormone receptor positive metastatic breast cancer Save
- Data from Novel Radiomic Measurements of Tumor-Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers Save
- Data from Novel Radiomic Measurements of Tumor-Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers Save
- Supplementary Data from Novel Radiomic Measurements of Tumor-Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers Save
- Supplementary Data from Novel Radiomic Measurements of Tumor-Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers Save
- Data from Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma Save
- Data from Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma Save
- Supplementary Document from Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma Save
- Supplementary Document from Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma Save
- Supplementary Sheet from Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma Save
- Supplementary Sheet from Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma Save
- Novel Radiomic Measurements of Tumor-Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers Save
- Predicting cancer outcomes with radiomics and artificial intelligence in radiology Save
- Radiomic Features Associated With HPV Status on Pretreatment Computed Tomography in Oropharyngeal Squamous Cell Carcinoma Inform Clinical Prognosis Save
- Radiomics For Surgical Planning and Prognostication. Save
- Radiomics-based assessment of ultra-widefield leakage patterns and vessel network architecture in the PERMEATE study: insights into treatment durability. Save
- Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma Save
- Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study Save
- Association of Peritumoral Radiomics With Tumor Biology and Pathologic Response to Preoperative Targeted Therapy for HER2 (ERBB2)-Positive Breast Cancer Save