Mohammadhadi Khorrami

Georgia Institute of Technology — United States

Medicine · Health Sciences

13h-index1.3kcitations89works1.42yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Radiomics and Machine Learning in Medical Imaging(73), Lung Cancer Diagnosis and Treatment(33), Gastric Cancer Management and Outcomes(13), Hepatocellular Carcinoma Treatment and Prognosis(10), Advanced X-ray and CT Imaging(10)

Publications89 total

A deep learning framework to iDentify prOgnostically releVant cancEr Regions (DOVER) within whole slide histopathology images
Cancer Letters·2025Open Access
Abstract 4366278: AI-Derived Cardiac Morphometrics from CAC CT for Heart Failure Risk Prediction
Circulation·2025
IMG-139. AI-Powered Classification of Tissue Sub-Compartments in Glioblastoma: Toward Quantitative Assessment of Tumor Heterogeneity
Neuro-Oncology·2025Open Access
IMGP-06. Radiomic Risk Stratification for Pediatric High-Grade Glioma
Neuro-Oncology·2025Open Access
Opportunities with artificial intelligence in assessing the potency of mesenchymal stromal cells
Stem Cells·2025· 1 citedOpen Access
95. AI-based early identification of nonresponders and surgical need in spinal tuberculosis via baseline MRI
The Spine Journal·2025Open Access
AI-informed computational pathology classifier predicts outcomes across treatment modalities in muscle-invasive urothelial carcinoma
Cancer Letters·2025· 1 citedOpen Access
QVT Score, a radiomic biomarker of vascular complexity, enables prognostication and monitoring of NSCLC immunotherapy
2025Open Access
Collagen disorder architecture features are associated with clinical, molecular, genetic factors and survival outcomes in colon cancer
npj Precision Oncology·2025Open Access
AI-based radiomic features predict outcomes and the added benefit of chemoimmunotherapy over chemotherapy in extensive stage small cell lung cancer: A multi-institutional study
Cancer Letters·2025· 4 cited
Computationally integrating radiology and pathology image features for predicting treatment benefit and outcome in lung cancer
npj Precision Oncology·2025· 8 citedOpen Access
Artificial Intelligence for Head and Neck Squamous Cell Carcinoma: From Diagnosis to Treatment
American Society of Clinical Oncology Educational Book·2025· 11 citedOpen Access
Radiomic signatures as predictors of pathological response to neoadjuvant chemoimmunotherapy in surgically resected NSCLC.
Journal of Clinical Oncology·2025
Association of radiomic features with disease-free survival following neoadjuvant chemoimmunotherapy in resectable NSCLC.
Journal of Clinical Oncology·2025
Leveraging AI predictive models to develop thymic tumor–specific peptides mimicking COL17A1 alterations.
Journal of Clinical Oncology·2025
Effect of fusion of radiomic, pathomic, and clinical biomarkers on multi-scale tumor biology and OS stratification in HNSCC receiving standard of care (SOC).
Journal of Clinical Oncology·2025· 1 cited
Computational pathology to predict docetaxel benefit for high-risk localized prostate cancer in NRG/RTOG 0521 (NCT00288080).
Journal of Clinical Oncology·2025· 1 cited
Radiomic phenotypes of tumor angiogenesis compared with PD-L1 in pre-treatment prediction of outcomes across immunotherapy regimens in NSCLC: An external validation study.
Journal of Clinical Oncology·2025
Quantitative and qualitative metrics of tumor stroma in predicting ovarian cancer outcomes and expansion of its study with AI-based tools
Molecular Therapy Oncology·2025· 1 citedOpen Access
Deep Learning Model of Primary Tumor and Metastatic Cervical Lymph Nodes From CT for Outcome Predictions in Oropharyngeal Cancer
JAMA Network Open·2025· 3 citedOpen Access
page 1 of 5Next →

Frequent Co-authors

Anant Madabhushi(34), Vamsidhar Velcheti(22), Pingfu Fu(22), Kaustav Bera(19), Amit Gupta(15), Pradnya D. Patil(15), Mehdi Alilou(14), Prantesh Jain(13), Vidya Sankar Viswanathan(13), Nathan A. Pennell(12), Rajat Thawani(9), Prateek Prasanna(8), Prabhakar Rajiah(8), Nathaniel Braman(6), Lukas Delasos(6), Germán Corredor(5), Pranjal Vaidya(5), Pushkar Mutha(5), Tilak Pathak(5), Robert Gilkeson(4)