Significant predictors were selected on the training set using recursive feature elimination methods, followed by prediction model development using 7 machine learning algorithms (logistic regression, ...

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...

Introduction Frailty is a common condition in older adults with diabetes, which significantly increases the risk of adverse health outcomes. Early identification of frailty in this population is ...

Background: Early identification of Type 1 Diabetes Mellitus (T1DM) in pediatric populations is crucial for implementing timely interventions and improving long-term outcomes. Peripheral blood ...

Background: Machine learning technology that uses available clinical data to predict diabetic retinopathy (DR) can be highly valuable in medical settings where fundus cameras are not accessible.

Nottingham Forest host Chelsea on the final day of the Premier League season. / Visionhaus / Getty Images Nottingham Forest and Chelsea are both fighting to finish in the top five and qualify for the ...

Objective: To characterize, via a predictive model using real-world data, patients with diabetes with a heightened probability of hospitalization. Methods: At the Endocrinology Unit of a tertiary ...

In a world saturated by artificial intelligence, Machine Learning, and over-zealous talks about both, it is important to understand and identify the types of Machine Learning we may encounter. For the ...