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Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks.

, , , , , , , and . MLHC, volume 106 of Proceedings of Machine Learning Research, page 381-405. PMLR, (2019)

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MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III., , , , , and . CHIL, page 222-235. ACM, (2020)Baselines for Chest X-Ray Report Generation., , , , , and . ML4H@NeurIPS, volume 116 of Proceedings of Machine Learning Research, page 126-140. PMLR, (2019)Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation., , , , , , and . CoRR, (2018)Cross-modal representation alignment of molecular structure and perturbation-induced transcriptional profiles., , , , and . PSB, WorldScientific, (2021)CheXclusion: Fairness gaps in deep chest X-ray classifiers., , , , and . PSB, WorldScientific, (2021)ACES: Automatic Cohort Extraction System for Event-Stream Datasets., , , and . CoRR, (2024)Clinically Accurate Chest X-Ray Report Generation., , , , , , and . MLHC, volume 106 of Proceedings of Machine Learning Research, page 249-269. PMLR, (2019)MEDS-Tab: Automated tabularization and baseline methods for MEDS datasets., , , , , , and . CoRR, (2024)Hurtful words: quantifying biases in clinical contextual word embeddings., , , , and . CHIL, page 110-120. ACM, (2020)Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different?, , , , , , , , , and . ML4H@NeurIPS, volume 116 of Proceedings of Machine Learning Research, page 1-9. PMLR, (2019)