102 citations · 147 across the 4 of their papers we have counts for
5 papers
Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts
Neeraj Wagh, Jionghao Wei, Samarth Rawal +2
The recent availability of large datasets in bio-medicine has inspired the development of representation learning methods for multiple healthcare applications. Despite advances in…
SCORE-IT: A Machine Learning-based Tool for Automatic Standardization of EEG Reports
Samarth Rawal, Yogatheesan Varatharajah
Machine learning (ML)-based analysis of electroencephalograms (EEGs) is playing an important role in advancing neurological care. However, the difficulties in automatically extract…
EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network
Neeraj Wagh, Yogatheesan Varatharajah
This paper presents a novel graph convolutional neural network (GCNN)-based approach for improving the diagnosis of neurological diseases using scalp-electroencephalograms (EEGs).…
Integrating Artificial Intelligence with Real-time Intracranial EEG Monitoring to Automate Interictal Identification of Seizure Onset Zones in Focal Epilepsy
Yogatheesan Varatharajah, Brent Berry, Jan Cimbalnik +6
An ability to map seizure-generating brain tissue, i.e., the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for pa…
A Contextual-bandit-based Approach for Informed Decision-making in Clinical Trials
Yogatheesan Varatharajah, Brent Berry, Sanmi Koyejo +1
Clinical trials involving multiple treatments utilize randomization of the treatment assignments to enable the evaluation of treatment efficacies in an unbiased manner. Such evalua…