Publications by authors named "Aimin Liao"
Objective: The aim of this study was to disseminate insights from a nationwide pilot of the International Classification of Diseases-11th revision (ICD-11).
Materials And Methods: The strategies and methodologies employed to implement the ICD-11 morbidity coding in 59 hospitals in China are described. The key considerations for the ICD-11 implementation were summarized based on feedback obtained from the pilot hospitals.
Cropland ecosystems are significant emission sources of NO, but a limited number of studies have focused on the impact of extreme weather events on NO fluxes from cropland. This present study integrated field observations and model simulations to explore the responses of NO fluxes to extreme weather events in typical rice and wheat rotation croplands in the middle and lower reaches of the Yangtze River (MLRYR) in China. The findings revealed that the studied rice-wheat rotation cropland exhibited a net source of NO over the three-year monitoring period, with annual cumulative NO emissions ranging from 190.
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- - The study focused on creating a predictive model for functional outcomes at discharge for patients with traumatic brain injury (TBI) using machine learning techniques.
- - Analyzing data from over 5,000 TBI patients, researchers used various models to determine which best predicted outcomes, finding that the random forest model performed the best in both internal and external validations.
- - Key predictors for better outcomes included the Barthel Index score at admission, age, treatment type, neurosurgery status, and existing comorbidities.
Article Synopsis
- Understanding soil water content (SWC) dynamics is essential for managing water and soil resources effectively, and this study focuses on a forested catchment in eastern China to analyze SWC's variability and stability.
- The Nandadish catchment, monitored from January 2017 to December 2019, had 34 sites measuring SWC, revealing that shallow soil layers experienced the most significant temporal changes, with dry years exhibiting greater spatial variability.
- Key factors like precipitation and temperature were found to influence SWC patterns, with precipitation affecting long-term variations and temperature influencing seasonal changes, highlighting the stability of SWC patterns and informing future soil moisture modeling.