Author of the publication

Changes during dialysis captured in electronic health records help predict near-term risk of sudden cardiac death.

, , and . AMIA, AMIA, (2013)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

 

Other publications of authors with the same name

A framework for the oversight and local deployment of safe and high-quality prediction models., , , , , , , , , and 3 other author(s). J. Am. Medical Informatics Assoc., 29 (9): 1631-1636 (2022)Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review., , , and . J. Am. Medical Informatics Assoc., 24 (1): 198-208 (2017)Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models., , , , , and . BMC Medical Informatics Decis. Mak., 22 (1): 108 (2022)A Systematic Review of Using Electronic Heath Records to Predict Clinical Events: Assessment of Opportunities and Challenges., , , and . CRI, AMIA, (2016)Adversarial Time-to-Event Modeling., , , , , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 734-743. PMLR, (2018)Understanding Algorithmic Bias in Clinical Prediction Models., , and . AMIA, AMIA, (2021)AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data., , , , , , and . J. Biomed. Informatics, (2022)AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data., , , , , , , , , and . CoRR, (2021)AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data., , , , , , and . CoRR, (2021)An outcome model approach to transporting a randomized controlled trial results to a target population., , , , , and . J. Am. Medical Informatics Assoc., 26 (5): 429-437 (2019)