Environmental pollution (Barking, Essex : 1987)
Nov 21, 2024
Accurate predictions of atmospheric particulate matter can be applied in providing services for air pollution prevention and control. However, the forecasting accuracy of traditional air quality models is limited owing to model uncertainties. In this...
IEEE transactions on bio-medical engineering
Nov 21, 2024
OBJECTIVE: Recent years have seen an increase in machine learning (ML)-based blood glucose (BG) forecasting models, with a growing emphasis on potential application to hybrid or closed-loop predictive glucose controllers. However, current approaches ...
Measles is an important infectious disease system both for its burden on public health and as an opportunity for studying nonlinear spatio-temporal disease dynamics. Traditional mechanistic models often struggle to fully capture the complex nonlinear...
Chronic Kidney Disease (CKD) represents a significant global health challenge, contributing to increased morbidity and mortality rates. This review paper explores the current landscape of machine learning (ML) techniques employed in CKD prediction an...
Environmental monitoring and assessment
Nov 19, 2024
The air quality index (AQI), based on criteria for air contaminants, is defined to provide a shared vision of air quality. As air pollution continues to rise in global cities due to urbanization and climate change, air pollution monitoring and foreca...
BACKGROUND: In concert with other digital technologies, artificial intelligence (AI) is shaping the vision of smart hospitals. The transformation into smart hospitals, however, is all but trivial due to the lack of financial and human resources, digi...
Global warming is becoming increasingly serious, with greenhouse gas (GHGs) emissions identified as a principal contributor. In response to the climate crisis, many countries are actively transitioning to renewable energy. Therefore, it is crucial to...
Given the global urgency to mitigate climate change, a key action is the development of effective carbon concentration reduction policies. To this end, an influential factor is the availability of accurate predictions of carbon concentration trends. ...
Numerous Deep Learning (DL) scenarios have been developed for evolving new healthcare systems that leverage large datasets, distributed computing, and the Internet of Things (IoT). However, the data used in these scenarios tend to be noisy, necessita...
In recent years, public health events have significantly impacted various aspects of human production and daily life, particularly in the domains of disease transmission and economic stability. While many scholars have primarily focused on the influe...
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