35 citations · 64 across the 14 of their papers we have counts for
5 papers · 1 filter
Mentality: A Mamba-based Approach towards Foundation Models for EEG
Saarang Panchavati, Corey Arnold, William Speier
This work explores the potential of foundation models, specifically a Mamba-based selective state space model, for enhancing EEG analysis in neurological disorder diagnosis. EEG, c…
Zero-shot Medical Event Prediction Using a Generative Pre-trained Transformer on Electronic Health Records
Ekaterina Redekop, Zichen Wang, Rushikesh Kulkarni +7
Longitudinal data in electronic health records (EHRs) represent an individual`s clinical history through a sequence of codified concepts, including diagnoses, procedures, medicatio…
Bidirectional Representation Learning from Transformers using Multimodal Electronic Health Record Data to Predict Depression
Yiwen Meng, William Speier, Michael K. Ong +1
Advancements in machine learning algorithms have had a beneficial impact on representation learning, classification, and prediction models built using electronic health record (EHR…
Semi-supervised Learning using Adversarial Training with Good and Bad Samples
Wenyuan Li, Zichen Wang, Yuguang Yue +4
In this work, we investigate semi-supervised learning (SSL) for image classification using adversarial training. Previous results have illustrated that generative adversarial netwo…
Semi-supervised learning based on generative adversarial network: a comparison between good GAN and bad GAN approach
Wenyuan Li, Zichen Wang, Jiayun Li +3
Recently, semi-supervised learning methods based on generative adversarial networks (GANs) have received much attention. Among them, two distinct approaches have achieved competiti…