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 ...

Background Anti-C1q autoantibodies can disrupt normal complement function, contributing to the formation of pathogenic immune ...

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

Researchers affiliated with Houston’s Methodist Hospital, Department of Otolaryngology, examined the link between recreational cannabis use and sinon | Cannabis Sciences ...

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...

A higher oxidative balance score (OBS), a composite indicator of pro- and antioxidant exposures, is associated with increased ...

Female sex at birth, age of 65 years or older, and 32 specific medications were identified as factors for drug-related candidiasis.

Researchers evaluated the impact of the timing of COVID-19 infection during pregnancy on both maternal illness severity and pregnancy outcomes.

Pregnant adolescents with SLE were more likely than healthy controls to have adverse pregnancy outcomes and more likely than ...

Familial clustering was identified in primary hyperparathyroidism, as first-degree relatives were at higher risk than control patients.

Specialty drugs, often used to treat complex conditions such as cancer or rare diseases, are among the most expensive treatments on the market. To make these drugs more affordable for payers, ...

Scientists have identified specific dietary patterns that may influence the risk of Parkinson’s disease (PD), a ...