Reliable and accurate streamflow forecasting plays a vital role in the optimal management of water resources. To improve the stability and accuracy of streamflow forecasting, a hybrid decomposition-ensemble model named VMD-LSTM-GBRT, which is sensiti...
Computational intelligence and neuroscience
Jan 10, 2022
With the decline of China's economic growth rate and the uproar of antiglobalization, the textile industry, one of the business cards of China's globalization, is facing a huge impact. When the economic model is undergoing transformation, it is more ...
Research output related to artificial intelligence (AI) in vascular diseases has been poorly investigated. The aim of this study was to evaluate scientific publications on AI in non-cardiac vascular diseases. A systematic literature search was conduc...
BACKGROUND: The exact risk assessment is crucial for the management of connective tissue disease-associated interstitial lung disease (CTD-ILD) patients. In the present study, we develop a nomogram to predict 3‑ and 5-year mortality by using machine ...
Liver Cancer is a threat to human health and life over the world. The key to reduce liver cancer incidence is to identify high-risk populations and carry out individualized interventions before cancer occurrence. Building predictive models based on m...
Journal of environmental sciences (China)
Jan 4, 2022
Air pollution is a major obstacle to future sustainability, and traffic pollution has become a large drag on the sustainable developments of future metropolises. Here, combined with the large volume of real-time monitoring data, we propose a deep lea...
International journal of computer assisted radiology and surgery
Jan 4, 2022
PURPOSE: Nowadays, the integration of Artificial intelligence algorithms and quantified radiographic imaging-based diagnostic procedures is hailing amplified deliberation particularly in assessment of skeletal maturity. So we intend to formulate a lo...
BMC medical informatics and decision making
Dec 31, 2021
BACKGROUND: Named entity recognition (NER) on Chinese electronic medical/healthcare records has attracted significantly attentions as it can be applied to building applications to understand these records. Most previous methods have been purely data-...
Deep learning techniques such as convolutional neural networks have largely improved the performance of building segmentation from remote sensing images. However, the images for building segmentation are often in the form of traditional orthophotos, ...
BMC medical informatics and decision making
Dec 27, 2021
BACKGROUND: Symptom phrase recognition is essential to improve the use of unstructured medical consultation corpora for the development of automated question answering systems. A majority of previous works typically require enough manually annotated ...
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