A5102812740- EEG and Brain-Computer Interfaces
- Neuroscience and Neural Engineering
- Customer Service Quality and Loyalty
- Blind Source Separation Techniques
- Voice and Speech Disorders
- Advanced Memory and Neural Computing
- Data Mining Algorithms and Applications
- Recommender Systems and Techniques
- Consumer Retail Behavior Studies
- Data Stream Mining Techniques
- Sentiment Analysis and Opinion Mining
- Bioinformatics and Genomic Networks
- Advanced Text Analysis Techniques
- Neural dynamics and brain function
- Online Learning and Analytics
- Parkinson's Disease Mechanisms and Treatments
- Technology Adoption and User Behaviour
- Gaze Tracking and Assistive Technology
- Digital Marketing and Social Media
- Gene expression and cancer classification
Iran University of Science and Technology
2010-2022
Parkinson’s disease (PD) is a complex neurodegenerative disease. Accurate diagnosis of this in the early stages crucial for its initial treatment. This paper aims to present comparative study on methods developed by machine learning techniques PD diagnosis. We rely clustering and prediction approaches perform study. Specifically, we use different data support vector regression ensembles predict Motor-UPDRS Total-UPDRS. The results are then compared with other approaches, multiple linear...
Measuring brain activity through Electroencephalogram (EEG) analysis for eye state prediction has attracted attention from machine learning researchers. There have been many methods EEG using supervised and unsupervised techniques. The tradeoff between the accuracy computation time of these in performing is an important issue that rarely investigated previous research. This paper accordingly proposes a new method signal Self-Organizing Map (SOM) clustering Deep Belief Network (DBN)...
Since EEG signals encode an individual’s intent of executing action, scientists have extensively focused on this topic. Motor Imagery (MI) been used by researchers to assistance disabled persons, for autonomous driving and even control devices such as wheelchairs. Therefore, accurate decoding these is essential develop a Brain–Computer interface (BCI) systems. Due dynamic nature, low signal-to-noise ratio complexity signals, not simple task. Extracting temporal spatial features from...
Achieving an efficient and reliable method is essential to interpret a user's brain wave deliver accurate response in biomedical signal processing. However, EEG patterns exhibit high variability across time uncertainty due noise it significant problem be addressed mental task as motor imagery. Therefore, fuzzy components may help enable higher tolerance noisy conditions. With the advent of Deep Learning its considerable contributions Artificial intelligence data analysis, numerous efforts...
Several non-supervised machine learning methods have been used in the analysis of gene expression data obtained from microarray experiments. Recently, biclustering, a approach that performs simultaneous clustering on row and column dimensions matrix, has shown to be remarkably effective variety applications. The discovery biclusters, which denote groups items show coherent values across subset all transactions set, is an important type performed real-valued sets various domains, such as...