Rate My Professor Fabien Scalzo

Scalzo's academic interests center on developing computational models for neuroimaging, where he has pioneered the integration of machine learning in stroke research and analysis. He has authored over 200 research papers, establishing a significant body of work in AI-driven medical imaging and neuroscience. Select key publications include "Peak detection in intracranial pressure signal waveforms: a comparative study" in Biomedical Engineering Online (2024), "Nodule Detection and Generation on Chest X-Rays: NODE21 Challenge" in IEEE Transactions on Medical Imaging (2024), "Prediction of visual field progression with serial optic disc photographs using deep learning" in the British Journal of Ophthalmology (2024), "Prediction of Hypoperfusion Lesion and Target Mismatch in Stroke from Diffusion-weighted MRI Using Deep Learning" in Radiology (2023), and "Mask R-CNN assisted 2.5D object detection pipeline of 68Ga-PSMA-11 PET/CT-positive metastatic pelvic lymph node after radical prostatectomy from solely CT imaging" in Scientific Reports (2023). As an investigator, he has contributed to neuroscience projects funded by the National Institutes of Health (NIH), National Science Foundation (NSF), American Heart Association (AHA), and Defense Advanced Research Projects Agency (DARPA). Scalzo serves as Associate Editor for Frontiers in Neurology and has been honored with the NSF China Young Scholar award and the BAEF fellowship. His research impacts clinical neurology, enhancing diagnostic tools through artificial intelligence.