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Algorithms to estimate Shapley value feature attributions
Feature attributions based on the Shapley value are popular for explaining machine
learning models. However, their estimation is complex from both theoretical and …
learning models. However, their estimation is complex from both theoretical and …
Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect
Mobile and wearable devices embedded with multiple sensors for health monitoring and
disease diagnosis are growing fields with the potential to provide efficient means for remote …
disease diagnosis are growing fields with the potential to provide efficient means for remote …
Status of deep learning for EEG-based brain–computer interface applications
In the previous decade, breakthroughs in the central nervous system bioinformatics and
computational innovation have prompted significant developments in brain–computer …
computational innovation have prompted significant developments in brain–computer …
[HTML][HTML] Deep learning and wearable sensors for the diagnosis and monitoring of Parkinson's disease: a systematic review
Parkinson's disease (PD) is a neurodegenerative disorder that produces both motor and non-
motor complications, degrading the quality of life of PD patients. Over the past two decades …
motor complications, degrading the quality of life of PD patients. Over the past two decades …
EEG-based brain-computer interfaces (BCIs): A survey of recent studies on signal sensing technologies and computational intelligence approaches and their …
Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact
with the environment. Recent advancements in technology and machine learning algorithms …
with the environment. Recent advancements in technology and machine learning algorithms …
Detection of Parkinson's disease from EEG signals using discrete wavelet transform, different entropy measures, and machine learning techniques
Early detection of Parkinson's disease (PD) is very important in clinical diagnosis for
preventing disease development. In this study, we present efficient discrete wavelet …
preventing disease development. In this study, we present efficient discrete wavelet …
Deep learning-based Parkinson's disease classification using vocal feature sets
H Gunduz - Ieee access, 2019 - ieeexplore.ieee.org
Parkinson's Disease (PD) is a progressive neurodegenerative disease with multiple motor
and non-motor characteristics. PD patients commonly face vocal impairments during the …
and non-motor characteristics. PD patients commonly face vocal impairments during the …
The state of the art of deep learning models in medical science and their challenges
With time, AI technologies have matured well and resonated in various domains of applied
sciences and engineering. The sub-domains of AI, machine learning (ML), deep learning …
sciences and engineering. The sub-domains of AI, machine learning (ML), deep learning …
[HTML][HTML] Deep convolutional neural network model for automated diagnosis of schizophrenia using EEG signals
A computerized detection system for the diagnosis of Schizophrenia (SZ) using a
convolutional neural system is described in this study. Schizophrenia is an anomaly in the …
convolutional neural system is described in this study. Schizophrenia is an anomaly in the …
Generative adversarial networks-based data augmentation for brain–computer interface
The performance of a classifier in a brain-computer interface (BCI) system is highly
dependent on the quality and quantity of training data. Typically, the training data are …
dependent on the quality and quantity of training data. Typically, the training data are …