A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

A freshman seminar encourages students to behave differently in the world and feel more passionately about biodiversity. Each Harvard University freshman in the “Tree” seminar must choose a single ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as the Framingham ...

Abstract: Developers typically build Machine Learning (ML) models for classification tasks in medical diagnosis. These models can make inferences from unseen data collected from sensors, aiding ...

Abstract: Various machine learning algorithms exist, each maintaining different assumptions about the underlying data or the function they aim to approximate. One such class of algorithms include tree ...

This study analyzed 1,544 diabetic patients from the First Affiliated Hospital of Shandong First Medical University, who were randomly divided into a training cohort (n = 1,082) and a testing cohort ...