Explainable artificial intelligence in Alzheimer's disease classification: A systematic review

V Viswan, N Shaffi, M Mahmud, K Subramanian… - Cognitive …, 2024 - Springer
The unprecedented growth of computational capabilities in recent years has allowed
Artificial Intelligence (AI) models to be developed for medical applications with remarkable …

Artificial intelligence for cognitive health assessment: state-of-the-art, open challenges and future directions

AR Javed, A Saadia, H Mughal, TR Gadekallu… - Cognitive …, 2023 - Springer
The subjectivity and inaccuracy of in-clinic Cognitive Health Assessments (CHA) have led
many researchers to explore ways to automate the process to make it more objective and to …

Machine Learning-based Evaluation of Heart Rate Variability Response in Children with Autism Spectrum Disorder

VA Mohammed, MA Mohammed… - … and Smart Energy …, 2023 - ieeexplore.ieee.org
At present, various electronic devices are used to monitor human heart rates. However, its
functions are to avoid predicting the problems caused by heart rate variability in advance …

State-of-the-art of stress prediction from heart rate variability using artificial intelligence

Y Haque, RS Zawad, CSA Rony, H Al Banna… - Cognitive …, 2024 - Springer
Recent advancements in the manufacturing and commercialisation of miniaturised sensors
and low-cost wearables have enabled an effortless monitoring of lifestyle by detecting and …

Comprehensive Analysis of Nature-Inspired Algorithms for Parkinson's Disease Diagnosis

S Shafiq, S Ahmed, MS Kaiser, M Mahmud… - IEEE …, 2022 - ieeexplore.ieee.org
Parkinson's disease (PD) is a prominent neurodegenerative disease that damages the
neurons of the substantia nigra, causing irreversible impairments leading to involuntary …

Enhancing biofeedback-driven self-guided virtual reality exposure therapy through arousal detection from multimodal data using machine learning

MA Rahman, DJ Brown, M Mahmud, M Harris… - Brain Informatics, 2023 - Springer
Virtual reality exposure therapy (VRET) is a novel intervention technique that allows
individuals to experience anxiety-evoking stimuli in a safe environment, recognise specific …

A Generic Review of Integrating Artificial Intelligence in Cognitive Behavioral Therapy

M Jiang, Q Zhao, J Li, F Wang, T He, X Cheng… - arXiv preprint arXiv …, 2024 - arxiv.org
Cognitive Behavioral Therapy (CBT) is a well-established intervention for mitigating
psychological issues by modifying maladaptive cognitive and behavioral patterns. However …

[HTML][HTML] iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems

S Azad, M Mahmud, KZ Zamli, MS Kaiser… - Expert Systems with …, 2024 - Elsevier
To meet the demand of the world's largest population, smart manufacturing has accelerated
the adoption of smart factories—where autonomous and cooperative instruments across all …

Privacy-preserving federated learning for pneumonia diagnosis

S Sarkar, S Agrawal, TR Gadekallu, M Mahmud… - … Conference on Neural …, 2022 - Springer
Early diagnosis of diseases has become the major focus of researchers today. Machine
Learning (ML) and Deep Learning (DL) algorithms have provided a much-needed boost to …

Stress Detection of Autistic Adults during Simulated Job Interviews Using a Novel Physiological Dataset and Machine Learning

M Migovich, D Adiani, M Breen, A Swanson… - ACM Transactions on …, 2024 - dl.acm.org
The interview process has been identified as one of the major barriers to employment of
autistic individuals, which contributes to the staggering rate of under and unemployment of …