AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data.
Journal:
Journal of biomedical informatics
Published Date:
Apr 11, 2022
Abstract
BACKGROUND: Medical decision-making impacts both individual and public health. Clinical scores are commonly used among various decision-making models to determine the degree of disease deterioration at the bedside. AutoScore was proposed as a useful clinical score generator based on machine learning and a generalized linear model. However, its current framework still leaves room for improvement when addressing unbalanced data of rare events.