1 citations · 1 across the 4 of their papers we have counts for
6 papers
An Interpretable AI Tool for SAVR vs TAVR in Low to Intermediate Risk Patients with Severe Aortic Stenosis
Vasiliki Stoumpou, Maciej Tysarowski, Talhat Azemi +4
Background. Treatment selection for low to intermediate risk patients with severe aortic stenosis between surgical (SAVR) and transcatheter (TAVR) aortic valve replacement remains…
Detection and Localization of Subdural Hematoma Using Deep Learning on Computed Tomography
Vasiliki Stoumpou, Rohan Kumar, Bernard Burman +3
Background. Subdural hematoma (SDH) is a common neurosurgical emergency, with increasing incidence in aging populations. Rapid and accurate identification is essential to guide tim…
Sparse Multiple Kernel Learning: Alternating Best Response and Semidefinite Relaxations
Dimitris Bertsimas, Caio de Prospero Iglesias, Nicholas A. G. Johnson
We study Sparse Multiple Kernel Learning (SMKL), which is the problem of selecting a sparse convex combination of prespecified kernels for support vector binary classification. Unl…
Adaptive Forests For Classification
Dimitris Bertsimas, Yubing Cui
Random Forests (RF) and Extreme Gradient Boosting (XGBoost) are two of the most widely used and highly performing classification and regression models. They aggregate equally weigh…
Holistic Artificial Intelligence in Medicine; improved performance and explainability
Periklis Petridis, Georgios Margaritis, Vasiliki Stoumpou +1
With the increasing interest in deploying Artificial Intelligence in medicine, we previously introduced HAIM (Holistic AI in Medicine), a framework that fuses multimodal data to so…
Multimodal Prescriptive Deep Learning
Dimitris Bertsimas, Lisa Everest, Vasiliki Stoumpou
We introduce a multimodal deep learning framework, Prescriptive Neural Networks (PNNs), that combines ideas from optimization and machine learning, and is, to the best of our knowl…