Dedicated Radiology K00 Postdoctoral Fellow at Harvard Medical School/Brigham and Women's Hospital, located in Boston, Massachusetts. My passion lies in research at the intersection of radiology, artificial intelligence, and precision medicine.
Machine Learning in Data-Scarce Domains: Leveraging advanced algorithms to address challenges in areas with limited data availability.
Early Detection of Lung Cancer: Harnessing deep learning techniques to detect and classify indeterminate pulmonary nodules, particularly those ranging from 4-20mm in diameter.
Pulmonary and Critical Care: Contributing to advancements in pulmonary care through innovative research and methodologies.
Current research revolves around amplifying the focus of Deep Neural Networks (DNN) on LDCT radiographic features acknowledged as being clinically relevant, in order to enhance the generalizability of a DNN to new images and improve network interpretability.
I hold a doctorate from the University of Vermont, where I was honored with NIH fellowships, including F31, T32, and F99. These fellowships were instrumental in advancing the classification accuracy of indeterminate pulmonary nodules. My overarching objective has been to mitigate patients' exposure to unnecessary invasive procedures and subsequent scans, thereby enhancing their quality of life.
For collaborations or inquiries, contact me at: amasquelin@bwh.harvard.edu.