Latest AI and machine learning research in health policy for healthcare professionals.
Federated learning holds great potential for enabling large-scale healthcare research and collaborat...
Real-world multi-agent decision-making systems often have to satisfy some constraints, such as harmf...
Medical image segmentation plays a crucial role in addressing emerging healthcare challenges. Althou...
Wearable devices with continuous monitoring capabilities are critical for the daily detection of epi...
For unknown nonlinear systems with state constraints, it is difficult to achieve the safe optimal co...
In the current era of digitalization and greenization, it is of great importance to explore how ente...
Accurate air pollution monitoring is critical to understand and mitigate the impacts of air pollutio...
OBJECTIVE: To develop models for prediction of the onset of specific diseases in cats using pet insu...
Deep reinforcement learning has achieved significant success in complex decision-making tasks. Howev...
In the context of the technological revolution and the digital intelligence era, the contradiction b...
Floods can severely impact the economy, environment and society. These impacts can be direct and ind...
In this study, an optimized comprehensive water quality index (WQI) model framework is developed, wh...
The swift progression of AI within the realm of medical devices has precipitated an imperative for s...
Continuous monitoring of patients' health facilitated by artificial intelligence (AI) has enhanced t...
Obstetric ultrasound (OBUS) is recommended as part of antenatal care for pregnant individuals worldw...
AIMS: We evaluated the cost-effectiveness of artificial intelligence (AI)-based diabetic retinopathy...
Early detection of breast cancer plays a crucial role in reducing the number of cases diagnosed at a...
The Internet of Things (IoT) connects various medical devices that enable remote monitoring, which c...
Efficiently extracting data from tables in the scientific literature is pivotal for building large-s...
This empirical study assessed the potential of developing a machine-learning model to identify child...
This study explores the potential for adapting AI-driven food waste management strategies from the h...