Author

Ghazal Azarfar

Observed names: G Azarfar, G. Azarfar

Institutions: University Health Network, University of Toronto, Toronto General Hospital Research Institute

Observed institutions: Carle Foundation Hospital, University Health Network, University of Illinois Urbana-Champaign, University of Toronto, University of Illinois System, University of Saskatchewan, Vector Institute, University of Wisconsin–Milwaukee, Toronto General Hospital Research Institute

ORCID: 0000-0002-8178-6169

Observed ORCID: 0000-0002-8178-6169

OpenAlex ID: A5020834852

Applications of deep learning to reduce the need for iodinated contrast media for CT imaging: a systematic review

2023 · Ghazal Azarfar, Seok-Bum Ko, et al. · International Journal of Computer Assisted Radiology and Surgery · 24

Responsible adoption of multimodal artificial intelligence in health care: promises and challenges

2025 · Ghazal Azarfar, Sara Naimimohasses, et al. · The Lancet Digital Health · 22

Deep learning-based age estimation from chest CT scans

2023 · Ghazal Azarfar, Seok-Bum Ko, et al. · International Journal of Computer Assisted Radiology and Surgery · 19

Estimating and correcting interference fringes in infrared spectra in infrared hyperspectral imaging

2018 · Ghazal Azarfar, Ebrahim Aboualizadeh, et al. · The Analyst · 17

Using machine learning for personalized prediction of longitudinal coronavirus disease 2019 vaccine responses in transplant recipients

2024 · Ghazal Azarfar, Yingji Sun, et al. · American Journal of Transplantation · 13

A multiagent large language model-based system to simulate the liver transplant selection committee: a retrospective cohort study

2026 · Bima J Hasjim, Ghazal Azarfar, et al. · The Lancet Digital Health · 9

2024 transplant AI symposium: key AI models shaping the future of transplant care

2026 · Annabel Koivu, Ghazal Azarfar, et al. · Frontiers in Transplantation · 2

Time lapse synchrotron IR chemical imaging for observing the acclimation of a single algal cell to CO2 treatment

2021 · Ghazal Azarfar, Ebrahim Aboualizadeh, et al. · Scientific Reports · 2

Machine learning model integrating transient elastography and clinical data for prediction of graft fibrosis after liver transplantation

2026 · Annabel Koivu, Ghazal Azarfar, et al. · World Journal of Hepatology · 1

Machine Learning–Based Evaluation of Combined EBV and CMV Serostatus as Predictors of Post-Transplant Lymphoproliferative Disorder

2026 · Ghazal Azarfar, Muath A. M. Alotaibi, et al. · Transplant International · 1

Poster Session I - A181 DEVELOPMENT OF AN IMPLEMENTABLE MULTIMODAL ARTIFICIAL INTELLIGENCE (AI) TOOL TO PREDICT HISTOLOGICAL RESPONSE IN LIVER TRANSPLANT RECIPIENTS WITH REJECTION

2026 · A Chinnadurai, M Enrizky Brillian, et al. · Journal of the Canadian Association of Gastroenterology

Machine Learning Models for Predicting Post-Transplant Lymphoproliferative Disease Risk: Insights from a Large-Scale Retrospective Cohort Study

2025 · G. Azarfar, M. Alotaibi, et al. · American Journal of Transplantation

Infrared chemical imaging for histologic interpretation of renal tissue

2021 · Ghazal Azarfar, Kianoush Falahkheirkhah, et al. · Advanced Chemical Microscopy for Life Science and Translational Medicine

Light Scattering in Diffraction Limit Infrared Imaging

2019 · Ghazal Azarfar · UWM Digital Commons (University of Wisconsin–Milwaukee)

Works count: 14

Citation count: 110

H-index: 6

I10-index: 5