Uncertainty Quantification in Detecting Choroidal Metastases on MRI via Evolutionary Strategies

no code implementations • 12 Apr 2024 • Bala McRae-Posani, Andrei Holodny, Hrithwik Shalu, Joseph N Stember

Given the challenges associated with acquiring large, annotated datasets in this field, there is a need for methods that enable uncertainty quantification in small data AI approaches tailored to radiology images.

Binary Classification Uncertainty Quantification

Deep neuroevolution to predict primary brain tumor grade from functional MRI adjacency matrices

no code implementations • 26 Nov 2022 • Joseph Stember, Mehrnaz Jenabi, Luca Pasquini, Kyung Peck, Andrei Holodny, Hrithwik Shalu

Whereas MRI produces anatomic information about the brain, functional MRI (fMRI) tells us about neural activity within the brain, including how various regions communicate with each other.

Deep reinforcement learning for fMRI prediction of Autism Spectrum Disorder

no code implementations • 17 Jun 2022 • Joseph Stember, Danielle Stember, Luca Pasquini, Jenabi Merhnaz, Andrei Holodny, Hrithwik Shalu

We hypothesized that a Deep Reinforcement Learning (DRL) classifier could learn effectively on a small fMRI training set.

reinforcement-learning Reinforcement Learning (RL)