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AutoScore-Ordinal: An Interpretable Machine Learning Framework for Generating Scoring Models for Ordinal Outcomes.

S. Saffari, Y. Ning, F. Xie, B. Chakraborty, V. Volovici, R. Vaughan, M. Ong, and N. Liu. AMIA, AMIA, (2022)

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Yilin Zhang

Yilin Zhou

Yilin Zhao

Yilin Vogel

Yilin Wang

Other publications of authors with the same name

Multiscale Bidirectional Diversity Entropy for Diesel Injector Fault-Type Diagnosis and Fault Degree Diagnosis.Y. Ke, E. Song, Y. Chen, C. Yao, and Y. Ning. IEEE Trans. Instrum. Meas., (2022)Feasibility of representing adherence to blood glucose monitoring through visualizations: A pilot survey study among healthcare workers.Y. Chen, S. Kao, M. Tan, Y. Ning, M. Salloway, W. Lin, K. Venkataraman, E. Hao, Y. Chow, E. Tai and 1 other author(s). Int. J. Medical Informatics, (2018)AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data.H. Yuan, F. Xie, M. Ong, Y. Ning, M. Chee, S. Saffari, H. Abdullah, B. Goldstein, B. Chakraborty, and N. Liu. CoRR, (2021)AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.F. Xie, Y. Ning, H. Yuan, B. Goldstein, M. Ong, N. Liu, and B. Chakraborty. CoRR, (2021)A translational perspective towards clinical AI fairness.M. Liu, Y. Ning, S. Teixayavong, M. Mertens, J. Xu, D. Ting, L. Cheng, J. Ong, Z. Teo, T. Tan and 5 other author(s). npj Digit. Medicine, (2023)AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.F. Xie, Y. Ning, H. Yuan, B. Goldstein, M. Ong, N. Liu, and B. Chakraborty. J. Biomed. Informatics, (2022)Research on Anti-Noise Performance of New Chaos Criterion.J. Cai, Y. Ning, W. Li, and L. Yao. DSA, page 503-504. IEEE, (2019)Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies.F. Xie, H. Yuan, Y. Ning, M. Ong, M. Feng, W. Hsu, B. Chakraborty, and N. Liu. J. Biomed. Informatics, (2022)Shapley variable importance cloud for machine learning models.Y. Ning, M. Liu, and N. Liu. CoRR, (2022)Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist.Y. Ning, S. Teixayavong, Y. Shang, J. Savulescu, V. Nagaraj, D. Miao, M. Mertens, D. Ting, J. Ong, M. Liu and 7 other author(s). CoRR, (2023)

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Disambiguation of "Ning, Yilin"

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AutoScore-Ordinal: An Interpretable Machine Learning Framework for Generating Scoring Models for Ordinal Outcomes.

Please choose a person to relate this publication to

Yilin Zhang

Yilin Zhou

Yilin Zhao

Yilin Vogel

Yilin Wang

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Ning, Yilin"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML AutoScore-Ordinal: An Interpretable Machine Learning Framework for Generating Scoring Models for Ordinal Outcomes.

Please choose a person to relate this publication to

Yilin Zhang

Yilin Zhou

Yilin Zhao

Yilin Vogel

Yilin Wang

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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AutoScore-Ordinal: An Interpretable Machine Learning Framework for Generating Scoring Models for Ordinal Outcomes.