Neural networks have been successfully employed in various domains such as
classification, regression and clustering, etc. Generally, the back propagation (BP) based …

This paper proposes a three-stage online deep learning model for time series based on the
ensemble deep random vector functional link (edRVFL). The edRVFL stacks multiple …

Discharge planning is integral to patient flow as delays can lead to hospital-wide
congestion. Because a structured discharge plan can reduce hospital length of stay while …

The vessel trajectory prediction plays a vital role in guaranteeing traffic safety for unmanned
surface vehicles and autonomous surface vessels. By leveraging advanced satellite …

The task of time series forecasting is to predict the future trend of data based on the collected
historical data, providing theoretical and data support for human judgment and decision …

Abstract Machine Learning (ML) systems are built to shift through large amounts of data.
Applying ML in production settings allows for the collection of additional data that can be …

Improving the accuracy of long-term multivariate time series forecasting is important for
practical applications. Various Transformer-based solutions emerging for time series …

Background Acute kidney injury (AKI) can make cases of acute respiratory distress
syndrome (ARDS) more complex, and the combination of the two can significantly worsen …

Background: Diabetic foot ulcers (DFUs) are serious complications of diabetes which can
lead to lower extremity amputations (LEAs). Risk prediction models can identify high-risk …

Time series analysis has been widely employed in various domains, including finance,
healthcare, meteorology, and economics. This approach is crucial in extracting patterns …