Background: Machine learning (ML) has been investigated for its predictive value in knee osteoarthritis (KOA) progression. However, systematic evidence on the effectiveness of ML is still lacking, ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

ABSTRACT: Background: Artificial intelligence (AI) technologies, including machine learning, natural language processing, and decision-support systems, are increasingly explored in primary care to ...

Abstract: This work investigates a hybrid quantum-classical machine learning methodology that combines deep learning with quantum computing to improve predictive analytics. The method starts by ...

Purpose: This study aimed to develop three types of machine learning (ML) models based on gradient boosting decision tree (GBDT), random forest (RF), and extreme gradient boosting (XGBoost) to explore ...

Abstract: Power distribution and generation schemes rely heavily on predictive maintenance to keep running smoothly and efficiently. Random Forests, Decision Trees, Support Vector Machines, besides ...

The goal of food safety is to ensure that the food provided to consumers does not represent a health risk due to the presence of chemical, physical, or biological hazards. In particular, microbial ...