A5096943348- Imbalanced Data Classification Techniques
- Health Systems, Economic Evaluations, Quality of Life
- Machine Learning in Healthcare
- Financial Distress and Bankruptcy Prediction
- Healthcare cost, quality, practices
- Medical Coding and Health Information
- Meta-analysis and systematic reviews
University Medical Center Utrecht
2024-2025
Heidelberg University
2024
University Hospital Heidelberg
2024
ABSTRACT Introduction Risk prediction models are increasingly used in healthcare to aid clinical decision‐making. In most contexts, model calibration (i.e., assessing the reliability of risk estimates) is critical. Data available for development often not perfectly balanced with modeled outcome individuals vs. without event interest equally prevalent data). It common researchers correct class imbalance, yet, effect such imbalance corrections on machine learning largely unknown. Methods We...
Risk prediction models are increasingly used in healthcare to aid clinical decision making. In most contexts, model calibration (i.e., assessing the reliability of risk estimates) is critical. Data available for development often not perfectly balanced with respect modeled outcome individuals vs. without event interest equally represented data). It common researchers correct this class imbalance, yet, effect such imbalance corrections on machine learning largely unknown. We studied a variety...