Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
Genomic surveillance—the process of monitoring and sequencing pathogens—is one of the most important tools for detecting ...
The human brain is known to naturally change with age, shrinking in size and volume after people reach their 30s or 40s. In ...
Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...
Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...
This paper proposes a hybrid machine learning framework for early diabetes prediction tailored to Sierra Leone, where locally representative datasets are scarce. The framework integrates Random Forest ...
Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear relationships ...
Nocturnal hypoglycemia (NH) is a common adverse event in elderly patients with type 2 diabetes (T2D). This study aims to develop a clinically applicable model for predicting the risk of NH in elderly ...
Abstract: This paper analyzes the performance of different LDA combinations with machine learning algorithms in predicting diabetes based on clinical data. The analysis involves patient records with ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
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