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Interpreting artificial intelligence models: a systematic review on the application of LIME and SHAP in Alzheimer's disease detection
Explainable artificial intelligence (XAI) has gained much interest in recent years for its ability
to explain the complex decision-making process of machine learning (ML) and deep …
to explain the complex decision-making process of machine learning (ML) and deep …
Explainable artificial intelligence in Alzheimer's disease classification: A systematic review
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 (AI) models to be developed for medical applications with remarkable …
State-of-the-art of stress prediction from heart rate variability using artificial intelligence
Recent advancements in the manufacturing and commercialisation of miniaturised sensors
and low-cost wearables have enabled an effortless monitoring of lifestyle by detecting and …
and low-cost wearables have enabled an effortless monitoring of lifestyle by detecting and …
Four-way classification of Alzheimer's disease using deep Siamese convolutional neural network with triplet-loss function
Alzheimer's disease (AD) is a neurodegenerative disease that causes irreversible damage
to several brain regions, including the hippocampus causing impairment in cognition …
to several brain regions, including the hippocampus causing impairment in cognition …
Artificial intelligence for cognitive health assessment: state-of-the-art, open challenges and future directions
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 …
many researchers to explore ways to automate the process to make it more objective and to …
ACCU3RATE: A mobile health application rating scale based on user reviews
Background Over the last decade, mobile health applications (mHealth App) have evolved
exponentially to assess and support our health and well-being. Objective This paper …
exponentially to assess and support our health and well-being. Objective This paper …
[HTML][HTML] Sustainable and intelligent time-series models for epidemic disease forecasting and analysis
There is an increasing risk of outbreaks escalating into epidemics, despite huge advances in
medical science. Epidemics like COVID-19, Monkeypox, Influenza and HIV have been …
medical science. Epidemics like COVID-19, Monkeypox, Influenza and HIV have been …
[HTML][HTML] Short-term prediction of COVID-19 cases using machine learning models
The first case in Bangladesh of the novel coronavirus disease (COVID-19) was reported on
8 March 2020, with the number of confirmed cases rapidly rising to over 175,000 by July …
8 March 2020, with the number of confirmed cases rapidly rising to over 175,000 by July …
Enhancing biofeedback-driven self-guided virtual reality exposure therapy through arousal detection from multimodal data using machine learning
Virtual reality exposure therapy (VRET) is a novel intervention technique that allows
individuals to experience anxiety-evoking stimuli in a safe environment, recognise specific …
individuals to experience anxiety-evoking stimuli in a safe environment, recognise specific …
Application of mathematical modeling in prediction of COVID-19 transmission dynamics
The entire world has been affected by the outbreak of COVID-19 since early 2020. Human
carriers are largely the spreaders of this new disease, and it spreads much faster compared …
carriers are largely the spreaders of this new disease, and it spreads much faster compared …