BACKGROUND: The increasing aging population and limited health care resources have placed new demands on the healthcare sector. Reducing the number of hospitalizations has become a political priority in many countries, and special focus has been dire...
BACKGROUND: While early mobilization is commonly implemented in intensive care unit treatment guidelines to improve functional outcome, the characterization of the optimal individual dosage (frequency, level or duration) remains unclear. The aim of t...
Coronavirus disease 2019 (COVID-19) spread worldwide and presented a significant threat to people's health. Inappropriate disease assessment and treatment strategies bring a heavy burden on healthcare systems. Our study aimed to construct predictive ...
BACKGROUND: Acute neurological complications are some of the leading causes of death and disability in the U.S. The medical professionals that treat patients in this setting are tasked with deciding where (e.g., home or facility), how, and when to di...
BMC medical informatics and decision making
Oct 22, 2022
BACKGROUND: Early prediction of patients' deterioration is helpful in early intervention for patients at greater risk of deterioration in Intensive Care Unit (ICU). This study aims to apply machine learning approaches to heterogeneous clinical data f...
We developed a machine learning algorithm to analyze trauma-related data and predict the mortality and chronic care needs of patients with trauma. We recruited admitted patients with trauma during 2015 and 2016 and collected their clinical data. Th...
Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease characterized by flares ranging from mild to life-threatening. Severe flares and complications can require hospitalizations, which account for most of the direct costs of SLE ca...