Environmental pollution (Barking, Essex : 1987)
Nov 28, 2024
Traditional statistical prediction methods on PM often focus on a single temporal or spatial dimension, with limited consideration for regional transport interactions among adjacent cities. To address this limitation, we propose a hybrid directed gra...
Techniques in vascular and interventional radiology
Nov 28, 2024
Artificial intelligence and robotics are transforming interventional radiology, driven by advancements in computer vision, robotics and procedural automation. Historically focused on diagnostics, AI now also enhances procedural capabilities in IR, en...
Environmental science and pollution research international
Nov 28, 2024
Monthly runoff forecasting plays a critically supportive role in water resources planning and management. Various signal decomposition techniques have been widely applied to enhance the accuracy of monthly runoff forecasting. However, the forecasting...
Environmental monitoring and assessment
Nov 27, 2024
Over time, computing power and storage resource advancements have enabled the widespread accumulation and utilization of data across various domains. In the field of air quality, analyzing data and developing air quality models have become pivotal in...
Environmental monitoring and assessment
Nov 23, 2024
The concentration of PM2.5 is one of the air quality indicators that the public pays the most attention to. Existing methods for PM2.5 prediction primarily analyze and forecast data from individual monitoring stations, without considering the mutual ...
Techniques in vascular and interventional radiology
Nov 22, 2024
Interventional Radiology is at the forefront of integrating advanced imaging techniques and minimally-invasive procedures to enhance patient care. The advent of Digital Health Technologies (DHTs), including artificial intelligence (AI), robotics, and...
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...