Aditi Chaurasia
Researcher
Also affiliated: National Institutes of Health (2024–2025); University of Arkansas Medical Center (2025); National Cancer Institute (2024–2025); Center for Cancer Research (2025); National Institutes of Health Clinical Center (2022–2024)
Faculty Researcher
Research Areas
Biomedical Subjects
Biography and Research Information
OverviewAI-generated summary
Aditi Chaurasia's research focuses on the application of advanced imaging and machine learning techniques for the detection and characterization of kidney tumors, particularly in the context of hereditary conditions like von Hippel-Lindau syndrome. Her work investigates the use of magnetic resonance imaging (MRI) in conjunction with radiomics and deep learning algorithms to predict tumor growth rates and non-invasively evaluate tumor grade.
Recent publications include the development of an MRI-based radiomics model for predicting clear cell renal cell carcinoma (RCC) growth in patients with von Hippel-Lindau syndrome, as well as deep learning models for hereditary clear cell RCC segmentation on MRI. She has also explored automated renal mass detection on contrast-enhanced MRI using deep learning algorithms like YOLOv7, and the development of predictive machine learning models for clear cell RCC growth using MRI data. Her collaborators include Shiva M. Singh, Ishan Pandey, Akhileshwar Reddy R Ginnaram, and Tarun Pandey, all from the University of Arkansas for Medical Sciences.
Metrics
- h-index: 4
- Publications: 10
- Citations: 39
Selected Publications
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Deciphering Wrist Pain: A Comprehensive MRI-Based Classification and Interpretation Approach (2025)
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Commentary: Leveraging Large Language Models for Radiology Education and Training (2025)
Collaboration Network
Top Collaborators
- Commentary: Leveraging Large Language Models for Radiology Education and Training
- Deciphering Wrist Pain: A Comprehensive MRI-Based Classification and Interpretation Approach
- Commentary: Leveraging Large Language Models for Radiology Education and Training
- Commentary: Leveraging Large Language Models for Radiology Education and Training
- Commentary: Leveraging Large Language Models for Radiology Education and Training
- Commentary: Leveraging Large Language Models for Radiology Education and Training
- Deciphering Wrist Pain: A Comprehensive MRI-Based Classification and Interpretation Approach
- Deciphering Wrist Pain: A Comprehensive MRI-Based Classification and Interpretation Approach
- Deciphering Wrist Pain: A Comprehensive MRI-Based Classification and Interpretation Approach
- Deciphering Wrist Pain: A Comprehensive MRI-Based Classification and Interpretation Approach
- Deciphering Wrist Pain: A Comprehensive MRI-Based Classification and Interpretation Approach
- Deciphering Wrist Pain: A Comprehensive MRI-Based Classification and Interpretation Approach
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