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Found 8 papers, 0 papers with code
Synthetic Data Generation Techniques for Developing AI-based Speech Assessments for Parkinson's Disease (A Comparative Study)
This paper explores using deep learning-based data generation techniques on the accuracy of machine learning classifiers that are the core of such systems.
AI-powered Language Assessment Tools for Dementia
The main objective of this paper is to propose an approach for developing an Artificial Intelligence (AI)-powered Language Assessment (LA) tool.
Meta-learning on Spectral Images of Electroencephalogram of Schizophenics
Schizophrenia is a complex psychiatric disorder involving changes in thought patterns, perception, mood, and behavior.
Transformer-Based Models for Question Answering on COVID19
In response to the Kaggle's COVID-19 Open Research Dataset (CORD-19) challenge, we have proposed three transformer-based question-answering systems using BERT, ALBERT, and T5 models.
Non-Pharmaceutical Intervention Discovery with Topic Modeling
We consider the task of discovering categories of non-pharmaceutical interventions during the evolving COVID-19 pandemic.
Brain Emotional Learning-based Prediction Model For the Prediction of Geomagnetic Storms
This study suggests a new data-driven model for the prediction of geomagnetic storm.
Emotion-Inspired Deep Structure (EiDS) for EEG Time Series Forecasting
Accurate forecasting of an electroencephalogram (EEG) time series is crucial for the correct diagnosis of neurological disorders such as seizures and epilepsy.
Brain Emotional Learning-Based Prediction Model (For Long-Term Chaotic Prediction Applications)
This study suggests a new prediction model for chaotic time series inspired by the brain emotional learning of mammals.
