BACKGROUND: Digital twins (DTs) represent a transformative advancement in radiology, integrating multimodal imaging, artificial intelligence (AI), and computational modeling to create dynamic, patient-specific virtual representations.
Recent advancements in artificial intelligence (AI) and traffic sensing technologies provide significant opportunities for real-time crash risk forecasting. While forecasting based on historical crash data yields macroscopic insights into future cras...
Anesthesiology has a longstanding commitment to patient safety, characterized by innovative research, quality improvement, multidisciplinary collaboration, and engineering-based approaches to care systems. The field has been instrumental in advancing...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Accurate traffic flow forecasting is critical for intelligent transportation systems, yet increasing model complexity in spatiotemporal graph neural networks does not always yield proportional gains. In this paper, we present a Bilinear Spatiotempora...
Accurate forecasting of ground-level ozone (O) is essential for assessing its public health and socioeconomic impacts. This study evaluates the performance of three deep learning models-Deep Convolutional Neural Networks (Deep-CNN), Long Short-Term M...
Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
Jun 10, 2025
When the epidemiology of infectious diseases is more complex, it is often difficult for disease prediction studies based on a single model to capture the multidimensional nature of disease transmission. In recent years, combining different models to ...
Cardiovascular disease (CVD) is a primary cause of death in India, accounting for a significant portion of the global CVD burden. This study looks at statistics on heart disease mortality from the Institute for Health Metrics and Evaluation (IHME) fr...
Proceedings of the National Academy of Sciences of the United States of America
Jun 10, 2025
The number of acutely food insecure people worldwide has doubled since 2017, increasing demand for early warning systems (EWS) that can predict food emergencies. Advances in computational methods, and the growing availability of near-real time remote...
Frequent occurrences of disasters such as red tides significantly threaten bay ecosystems, making near real-time water quality forecasting crucial for disaster warning and decision-making. Conventional techniques, such as process-based modeling and i...
BACKGROUND: Amidst a backdrop of crisis in primary healthcare, characterised by increasing patient demands and a stagnant workforce, artificial intelligence (AI) is proposed as a potential enhancer of clinical efficacy and decision-making support. In...
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