The ability to anticipate glucose changes before they happen is one of ML’s biggest contributions to CGM. Predictive models ...

Tanuj Mathur uses AI and machine learning to create a cybersecurity framework, improving patch management, regulatory ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

This approach guarantees a rigorous, clinically relevant, and actionable evaluation for decision-makers and would allow us to assess both the technical performance of the models used and their ...

To our knowledge, to date, however, there are no widely utilized machine learning (ML) models that predict development of CLL. Therefore, the objective of this study was to leverage readily available ...

Tree species classification using machine learning and deep learning models of single tree point cloud data. The final step involves analyzing and evaluating the classification results.

This study investigates the application of adaptive decision tree models for predicting student performance, focusing on their role in educational data mining and adaptive learning. A major challenge ...

It guides users through a decision-making process to identify suitable machine learning algorithms for their specific tasks: regression, classification, time series forecasting, clustering, ...

I show how AI tool (Decision Tree tool) could be used to expose to the public parts of personal privacy. In this study, I show how it is possible, by analyzing a large database and using Data Minnig ...

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...