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- 10564463 type SIO_001066 assertion.
- 10564463 label "Addressing the Challenge of Missing Medical Data in Healthcare Analytics: A Focus on Machine Learning Predictions for ICU Length of Stay" assertion.
- 10564463 seeAlso 10564463 assertion.
- 10564463 description "This research investigates the impact of missing data on the performance of machine learning algorithms, with a particular focus on the MIMIC-IV dataset. This project aims to investigate the extent to which missing data negatively impacts the training of machine learning algorithms, and whether demographic groups with a higher proportion of missing data (i.e.,ethnicity) have lower predictive accuracy. Using advanced machine learning and data analysis techniques, the results highlight important considerations related to missing data in medical datasets and provide useful insights for improving predictive modeling and decision support systems in clinical practice offers." assertion.
- 10564463 about Q2539 assertion.
- 10564463 about Q1916557 assertion.