Development of a COVID-19 early risk assessment system based on multiple machine learning algorithms and routine blood tests: a real-world study.

Backgrounds: During the Coronavirus Disease 2019 (COVID-19) epidemic, the massive spread of the disease has placed an enormous burden on the world's healthcare and economy. The early risk assessment system based on a variety of machine learning (ML) algorithms may be able to provide more accurate advice on the classification of COVID-19 patients, offering predictive, preventive, and personalized medicine (PPPM) solutions in the future.

Methods: In this retrospective study, we divided a portion of the data into training and validation cohorts in a 7:3 ratio and established a model based on a combination of two ML algorithms first.

Machine learning-based derivation and validation of three immune phenotypes for risk stratification and prognosis in community-acquired pneumonia: a retrospective cohort study.

Background: The clinical presentation of Community-acquired pneumonia (CAP) in hospitalized patients exhibits heterogeneity. Inflammation and immune responses play significant roles in CAP development. However, research on immunophenotypes in CAP patients is limited, with few machine learning (ML) models analyzing immune indicators.

Mesenchymal Stromal Cell Therapy Alleviates Ovalbumin-Induced Chronic Airway Remodeling by Suppressing M2 Macrophage Polarization.

Chronic asthma is characterized by airway hyperresponsiveness, inflammation, and remodeling. Previous studies have shown that mesenchymal stromal/stem cells (MSCs) exert anti-inflammatory effects on asthma via regulation of the immune cells. However, the therapeutic mechanism of MSCs, especially the mechanism of airway remodeling in chronic asthma, remains to be elucidated.

A Diagnostic Model for Alzheimer's Disease Based on Blood Levels of Autophagy-Related Genes.

Alzheimer's disease (AD) is a common neurodegenerative disease. The major problems that exist in the diagnosis of AD include the costly examinations and the high-invasive sampling tissue. Therefore, it would be advantageous to develop blood biomarkers.