Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

Objectives Cardiopulmonary involvement (CPI) is a major cause of morbidity and mortality in systemic sclerosis (SSc). The 6 min walk test (6MWT) is widely used to assess functional capacity, but its ...

The elimination of the latent viral reservoir remains the main barrier in the quest for a cure for people with HIV (PWH). The administration of latency reversal agents (LRA) at antiretroviral ...

Plasma proteomics reveals that the biological ages of key organs, especially the brain and immune system, strongly predict ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

Objective This study aimed to assess the coronavirus disease 2019 (COVID-19) hospitalisation costs and its associated factors on Nepalese households during the second wave of the pandemic, within the ...

To address the challenges of traditional marine meteorological prediction methods, which struggle to effectively capture intervariable correlations in multivariate time series data and suffer from ...

This need is putting the spotlight back on traceability, which is fundamental to building confidence in complex systems.

Compared with the multivariate linear and multivariate nonlinear fitting results, the fitting accuracy of the T-BP neural network model is significantly improved.

This study introduces a Q-learning-based nonlinear model predictive control (QL-NMPC) framework for temperature control in batch reactors. A reinforcement learning agent is trained in simulation to ...

Multivariate Segment Expandable Encoder-Decoder Model for Time Series Forecasting Abstract: Accurate time series forecasting is critical in a variety of fields, including transportation, weather ...