A review on VANET research: Perspective of recent emerging technologies

MJN Mahi, S Chaki, S Ahmed, M Biswas… - IEEE …, 2022 - ieeexplore.ieee.org
Recent technology has modeled VANET (vehicular adhoc network) communication well in
terms of privileges to derive vehicular communication technologically to save time, energy …

[HTML][HTML] The definitions of health apps and medical apps from the perspective of public health and law: qualitative analysis of an interdisciplinary literature overview

L Maaß, M Freye, CC Pan, HH Dassow… - JMIR mHealth and …, 2022 - mhealth.jmir.org
Background The terms health app and medical app are often used interchangeably but do
not necessarily mean the same thing. To better understand these terms and better regulate …

Exploring the factors that affect user experience in mobile-health applications: A text-mining and machine-learning approach

S Pal, B Biswas, R Gupta, A Kumar, S Gupta - Journal of Business …, 2023 - Elsevier
Recent years have witnessed an increased demand for mobile health (mHealth) platforms
owing to the COVID-19 pandemic and preference for doorstep delivery. However, factors …

Four-way classification of Alzheimer's disease using deep Siamese convolutional neural network with triplet-loss function

F Hajamohideen, N Shaffi, M Mahmud, K Subramanian… - Brain Informatics, 2023 - Springer
Alzheimer's disease (AD) is a neurodegenerative disease that causes irreversible damage
to several brain regions, including the hippocampus causing impairment in cognition …

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 …

Detecting COVID-19 infection status from chest X-ray and CT scan via single transfer learning-driven approach

P Ghose, M Alavi, M Tabassum, M Ashraf Uddin… - Frontiers in …, 2022 - frontiersin.org
COVID-19 has caused over 528 million infected cases and over 6.25 million deaths since its
outbreak in 2019. The uncontrolled transmission of the SARS-CoV-2 virus has caused …

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 …

Interpreting artificial intelligence models: a systematic review on the application of LIME and SHAP in Alzheimer's disease detection

V Vimbi, N Shaffi, M Mahmud - Brain Informatics, 2024 - Springer
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 …

[PDF][PDF] Deep learning in agriculture: a review

P Bharman, SA Saad, S Khan, I Jahan… - Asian Journal of …, 2022 - researchgate.net
Deep learning (DL) is a kind of sophisticated data analysis and image processing
technology, with good results and great potential. DL has been applied to many different …