Machine and deep learning for longitudinal biomedical data: a review of methods and applications

A Cascarano, J Mur-Petit… - Artificial Intelligence …, 2023 - Springer
Exploiting existing longitudinal data cohorts can bring enormous benefits to the medical
field, as many diseases have a complex and multi-factorial time-course, and start to develop …

Human action recognition in smart living services and applications: context awareness, data availability, personalization, and privacy

G Diraco, G Rescio, A Caroppo, A Manni, A Leone - Sensors, 2023 - mdpi.com
Smart living, an increasingly prominent concept, entails incorporating sophisticated
technologies in homes and urban environments to elevate the quality of life for citizens. A …

Advancing fake news detection: hybrid deep learning with fasttext and explainable AI

E Hashmi, SY Yayilgan, MM Yamin, S Ali… - IEEE …, 2024 - ieeexplore.ieee.org
The widespread propagation of misinformation on social media platforms poses a significant
concern, prompting substantial endeavors within the research community to develop robust …

Variable-complexity machine learning models for large-scale oil spill detection: The case of Persian Gulf

S Najafizadegan, M Danesh-Yazdi - Marine Pollution Bulletin, 2023 - Elsevier
Oil spill is the main cause of marine pollution in the waterbodies with rich oil resources. In
this study, we developed and compared the performance of variable-complexity machine …

Pediatric intensive care unit treatment alters the diversity and composition of the gut microbiota and antimicrobial resistance gene expression in critically ill children

J Xu, X Kong, J Li, H Mao, Y Zhu, X Zhu… - Frontiers in …, 2023 - frontiersin.org
Introduction Common critical illnesses are a growing economic burden on healthcare
worldwide. However, therapies targeting the gut microbiota for critical illnesses have not …

Investigating the interaction parameters on ventilation supercavitation phenomena: Experimental and numerical analysis with machine learning interpretation

HA Kamali, M Pasandidehfard - Physics of Fluids, 2023 - pubs.aip.org
Understanding the optimal values and interactions of parameters within each process is of
highest importance. This study is dedicated to exploring the influence of various parameters …

The Rapid Non-Destructive Differentiation of Different Varieties of Rice by Fluorescence Hyperspectral Technology Combined with Machine Learning

Z Kang, R Fan, C Zhan, Y Wu, Y Lin, K Li, R Qing, L Xu - Molecules, 2024 - mdpi.com
A rice classification method for the fast and non-destructive differentiation of different
varieties is significant in research at present. In this study, fluorescence hyperspectral …

Dust detection and susceptibility mapping by aiding satellite imagery time series and integration of ensemble machine learning with evolutionary algorithms

SV Razavi-Termeh, A Sadeghi-Niaraki, RA Naqvi… - Environmental …, 2023 - Elsevier
To mitigate the impact of dust on human health and the environment, it is crucial to create a
model and map that identifies the areas susceptible to dust. The present study focused on …

Quantifying the effect of socio-economic-geo drivers on the change of municipal waste disposal in China by an integrated TWFE-PRF-SDM methodology

P Yao, B Li, S Zhang, L Song, J Tai, J Zhao… - Journal of …, 2023 - Elsevier
Municipal solid waste management and disposal in China have significantly evolved since
2000. Due to China's vast land area and significant socioeconomic and geographic …

Classification of parkinson disease with feature selection using genetic algorithm

M Iftikhar, N Ali, RH Ali, A Bais - 2023 IEEE Canadian …, 2023 - ieeexplore.ieee.org
Parkinson's disease is a complex neurological disorder that affects various neural,
behavioural, and physiological systems. To provide optimal treatment and improve patient …