Application of artificial intelligence in wearable devices: Opportunities and challenges

D Nahavandi, R Alizadehsani, A Khosravi… - Computer Methods and …, 2022 - Elsevier
Background and objectives: Wearable technologies have added completely new and fast
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …

Opportunities and challenges in explainable artificial intelligence (xai): A survey

A Das, P Rad - arxiv preprint arxiv:2006.11371, 2020 - arxiv.org
Nowadays, deep neural networks are widely used in mission critical systems such as
healthcare, self-driving vehicles, and military which have direct impact on human lives …

[HTML][HTML] Explaining deep neural networks: A survey on the global interpretation methods

R Saleem, B Yuan, F Kurugollu, A Anjum, L Liu - Neurocomputing, 2022 - Elsevier
A substantial amount of research has been carried out in Explainable Artificial Intelligence
(XAI) models, especially in those which explain the deep architectures of neural networks. A …

[HTML][HTML] A state-of-the-art survey on deep learning theory and architectures

MZ Alom, TM Taha, C Yakopcic, S Westberg, P Sidike… - electronics, 2019 - mdpi.com
In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …

Multiple classification of brain MRI autism spectrum disorder by age and gender using deep learning

HS Nogay, H Adeli - Journal of Medical Systems, 2024 - Springer
The fact that the rapid and definitive diagnosis of autism cannot be made today and that
autism cannot be treated provides an impetus to look into novel technological solutions. To …

Deep learning for neuroimaging-based diagnosis and rehabilitation of autism spectrum disorder: a review

M Khodatars, A Shoeibi, D Sadeghi… - Computers in biology …, 2021 - Elsevier
Abstract Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …

Diagnostic of autism spectrum disorder based on structural brain MRI images using, grid search optimization, and convolutional neural networks

HS Nogay, H Adeli - Biomedical Signal Processing and Control, 2023 - Elsevier
In this study, an automatic autism diagnostic model based on sMRI is proposed. This
proposed model consists of two basic stages. The first stage is the preprocessing stage …

Multi-head CNN–RNN for multi-time series anomaly detection: An industrial case study

M Canizo, I Triguero, A Conde, E Onieva - Neurocomputing, 2019 - Elsevier
Detecting anomalies in time series data is becoming mainstream in a wide variety of
industrial applications in which sensors monitor expensive machinery. The complexity of this …

Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging

HS Nogay, H Adeli - Reviews in the Neurosciences, 2020 - degruyter.com
Autism spectrum disorder (ASD) is a neurodevelopmental incurable disorder with a long
diagnostic period encountered in the early years of life. If diagnosed early, the negative …

Machine learning‐enabled smart sensor systems

N Ha, K Xu, G Ren, A Mitchell… - Advanced Intelligent …, 2020 - Wiley Online Library
Recent advancements and major breakthroughs in machine learning (ML) technologies in
the past decade have made it possible to collect, analyze, and interpret an unprecedented …