Algorithms to estimate Shapley value feature attributions

H Chen, IC Covert, SM Lundberg, SI Lee - Nature Machine Intelligence, 2023 - nature.com
Feature attributions based on the Shapley value are popular for explaining machine
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

CV Anikwe, HF Nweke, AC Ikegwu… - Expert Systems with …, 2022 - Elsevier
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 …

Status of deep learning for EEG-based brain–computer interface applications

KM Hossain, MA Islam, S Hossain, A Nijholt… - Frontiers in …, 2023 - frontiersin.org
In the previous decade, breakthroughs in the central nervous system bioinformatics and
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

L Sigcha, L Borzì, F Amato, I Rechichi… - Expert Systems with …, 2023 - Elsevier
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 …

EEG-based brain-computer interfaces (BCIs): A survey of recent studies on signal sensing technologies and computational intelligence approaches and their …

X Gu, Z Cao, A Jolfaei, P Xu, D Wu… - … /ACM transactions on …, 2021 - ieeexplore.ieee.org
Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact
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

M Aljalal, SA Aldosari, M Molinas, K AlSharabi… - Scientific Reports, 2022 - nature.com
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 …

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 …

The state of the art of deep learning models in medical science and their challenges

C Bhatt, I Kumar, V Vijayakumar, KU Singh… - Multimedia Systems, 2021 - Springer
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 …

[HTML][HTML] Deep convolutional neural network model for automated diagnosis of schizophrenia using EEG signals

SL Oh, J Vicnesh, EJ Ciaccio, R Yuvaraj, UR Acharya - Applied Sciences, 2019 - mdpi.com
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 …

Generative adversarial networks-based data augmentation for brain–computer interface

F Fahimi, S Dosen, KK Ang… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
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 …