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Yilin Ning

Showing results (11-20 of 54) with videos related to

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Journal of Biomedical Informatics|November 26, 2021
AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival dataFeng Xie, Yilin Ning, Han Yuan, et al.
Journal of Biomedical Informatics|January 2, 2022
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologiesFeng Xie, Han Yuan, Yilin Ning, et al.
Patterns (New York, N.Y.)|November 21, 2024
FAIM: Fairness-aware interpretable modeling for trustworthy machine learning in healthcareMingxuan Liu, Yilin Ning, Yuhe Ke, et al.
PLOS Digital Health|February 22, 2023
A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort studyYilin Ning, Siqi Li, Marcus Eng Hock Ong, et al.
Studies in Health Technology and Informatics|August 8, 2025
FairFML: A Unified Approach to Algorithmic Fair Federated Learning with Applications to Reducing Gender Disparities in Cardiac Arrest OutcomesSiqi Li, Qiming Wu, Xin Li, et al.
Clinical and Experimental Emergency Medicine|April 3, 2026
Integrating the interpretable machine learning Score For Emergency Risk Prediction (SERP) with emergency department triage to better predict 30-Day mortalityYvonne Wong Qi Feng, Yohei Okada, Stephanie Fook-Chong, et al.
BMC Medical Research Methodology|November 5, 2022
AutoScore-Ordinal: an interpretable machine learning framework for generating scoring models for ordinal outcomesSeyed Ehsan Saffari, Yilin Ning, Feng Xie, et al.
Health Data Science|April 22, 2026
Survival Modeling Using Deep Learning, Machine Learning, and Statistical Methods: A Comparative Analysis for Predicting Mortality After Hospital AdmissionZiwen Wang, Jin Wee Lee, Tanujit Chakraborty, et al.
Patterns (New York, N.Y.)|April 25, 2022
Shapley variable importance cloud for interpretable machine learningYilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, et al.
Emergency Medicine Journal : EMJ|May 29, 2025
Association between age and length of stay in the emergency department in a tertiary care hospital: a retrospective observational studyPrachur Khandelwal, Yohei Okada, Yilin Ning, et al.
Pageof 6

Showing results (11-20 of 54) with videos related to

Sort By:
Pageof 6
Journal of Biomedical Informatics|November 26, 2021
AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival dataFeng Xie, Yilin Ning, Han Yuan, et al.
Journal of Biomedical Informatics|January 2, 2022
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologiesFeng Xie, Han Yuan, Yilin Ning, et al.
Patterns (New York, N.Y.)|November 21, 2024
FAIM: Fairness-aware interpretable modeling for trustworthy machine learning in healthcareMingxuan Liu, Yilin Ning, Yuhe Ke, et al.
PLOS Digital Health|February 22, 2023
A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort studyYilin Ning, Siqi Li, Marcus Eng Hock Ong, et al.
Studies in Health Technology and Informatics|August 8, 2025
FairFML: A Unified Approach to Algorithmic Fair Federated Learning with Applications to Reducing Gender Disparities in Cardiac Arrest OutcomesSiqi Li, Qiming Wu, Xin Li, et al.
Clinical and Experimental Emergency Medicine|April 3, 2026
Integrating the interpretable machine learning Score For Emergency Risk Prediction (SERP) with emergency department triage to better predict 30-Day mortalityYvonne Wong Qi Feng, Yohei Okada, Stephanie Fook-Chong, et al.
BMC Medical Research Methodology|November 5, 2022
AutoScore-Ordinal: an interpretable machine learning framework for generating scoring models for ordinal outcomesSeyed Ehsan Saffari, Yilin Ning, Feng Xie, et al.
Health Data Science|April 22, 2026
Survival Modeling Using Deep Learning, Machine Learning, and Statistical Methods: A Comparative Analysis for Predicting Mortality After Hospital AdmissionZiwen Wang, Jin Wee Lee, Tanujit Chakraborty, et al.
Patterns (New York, N.Y.)|April 25, 2022
Shapley variable importance cloud for interpretable machine learningYilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, et al.
Emergency Medicine Journal : EMJ|May 29, 2025
Association between age and length of stay in the emergency department in a tertiary care hospital: a retrospective observational studyPrachur Khandelwal, Yohei Okada, Yilin Ning, et al.
Pageof 6