☆ 4.7 Article

Effects of dataset size and interactions on the prediction performance of logistic regression and deep learning models

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2022)

A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Moloud Abdar et al.

Summary: Uncertainty quantification (UQ) methods are essential in reducing uncertainties in optimization and decision making processes. Bayesian approximation and ensemble learning techniques are widely used types of UQ methods.

INFORMATION FUSION (2021)

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Article Multidisciplinary Sciences

Comparison of deep learning with traditional models to predict preventable acute care use and spending among heart failure patients

Maor Lewis et al.

Summary: Recent health reforms incentivize cardiologists and accountable care organizations to participate in value-based care models for heart failure (HF). This study compared deep learning approaches with traditional logistic regression to predict preventable utilization among HF patients. The results showed that deep learning models consistently outperformed LR for all three outcomes, offering a promising approach to identify patients for targeted interventions.

SCIENTIFIC REPORTS (2021)

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Article Allergy