Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

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, ...

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 ...

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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 ...

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...

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.

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...