Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

A machine learning model using basic clinical data can predict PH risk, identifying key predictors like low hemoglobin and elevated NT-proBNP. Researchers have developed a machine learning model that ...

Conclusions: There is a potential mismatch between what clinicians identify as important in determining palliative care need and final eligibility determinations. Patients with dementia were less ...

Sepsis ranks among the deadliest illnesses a child can face. It’s an infection that spirals out of control, causing organ ...

Machine learning models using initial neuropsychological and neuropsychiatric clinical data accurately distinguished AD from bvFTD.

Prenatal lead exposure was associated with a significantly increased risk for major depressive disorder (MDD) in adulthood, ...

A higher oxidative balance score is associated with increased odds of allergic rhinitis in an adjusted analysis.

The EnABLE Social Inclusion Framework for Results-Based Climate Finance Initiatives was devised as a key input into the Social Inclusion Strategy and Action Plan of the Enhancing Access to Benefits ...

Among adolescent girls with concussion, greater initial emotional symptom severity, reflected in higher anxiety, depression, and sleep disturbance scores, was associated with a higher likelihood of ...

Growing connectedness since 2008 may have deepened social and political divides. More friends could mean more conflict—and less tolerance.

An analysis of 5 machine-learning algorithms identified predictors for moderate-to-severe cancer-related fatigue in patients with CRC undergoing chemotherapy.