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ORCIDYilin Ning
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2020 – today
- 2024
[j12]Rui Yang
, Sabarinath Vinod Nair, Yuhe Ke, Danny D'Agostino, Mingxuan Liu, Yilin Ning, Nan Liu:
Disparities in clinical studies of AI enabled applications from a global perspective. npj Digit. Medicine 7(1) (2024)- [j11]Mingxuan Liu, Yilin Ning, Yuhe Ke, Yuqing Shang, Bibhas Chakraborty, Marcus Eng Hock Ong, Roger Vaughan, Nan Liu:
FAIM: Fairness-aware interpretable modeling for trustworthy machine learning in healthcare. Patterns 5(10): 101059 (2024) - [i21]Siqi Li, Yuqing Shang, Ziwen Wang, Qiming Wu, Chuan Hong, Yilin Ning, Di Miao, Marcus Eng Hock Ong, Bibhas Chakraborty, Nan Liu:
Developing Federated Time-to-Event Scores Using Heterogeneous Real-World Survival Data. CoRR abs/2403.05229 (2024) - [i20]Mingxuan Liu, Yilin Ning, Yuhe Ke, Yuqing Shang, Bibhas Chakraborty, Marcus Eng Hock Ong, Roger Vaughan, Nan Liu:
Fairness-Aware Interpretable Modeling (FAIM) for Trustworthy Machine Learning in Healthcare. CoRR abs/2403.05235 (2024) - [i19]Ziwen Wang, Jin Wee Lee, Tanujit Chakraborty, Yilin Ning, Mingxuan Liu, Feng Xie, Marcus Eng Hock Ong, Nan Liu:
Survival modeling using deep learning, machine learning and statistical methods: A comparative analysis for predicting mortality after hospital admission. CoRR abs/2403.06999 (2024) - [i18]Mingxuan Liu, Yilin Ning, Salinelat Teixayavong, Xiaoxuan Liu, Mayli Mertens, Yuqing Shang, Xin Li, Di Miao, Jie Xu, Daniel Shu Wei Ting, Lionel Tim-Ee Cheng, Jasmine Chiat Ling Ong, Zhen Ling Teo, Ting Fang Tan, Narrendar RaviChandran, Fei Wang, Leo Anthony Celi, Marcus Eng Hock Ong, Nan Liu:
Towards Clinical AI Fairness: Filling Gaps in the Puzzle. CoRR abs/2405.17921 (2024) - [i17]Rui Yang, Yilin Ning, Emilia Keppo, Mingxuan Liu, Chuan Hong, Danielle S. Bitterman, Jasmine Chiat Ling Ong, Daniel Shu Wei Ting, Nan Liu:
Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine. CoRR abs/2406.12449 (2024) - [i16]Siqi Li, Xin Li, Kunyu Yu, Di Miao, Mingcheng Zhu, Mengying Yan, Yuhe Ke, Danny D'Agostino, Yilin Ning, Qiming Wu, Ziwen Wang, Yuqing Shang, Molei Liu, Chuan Hong, Nan Liu:
Bridging Data Gaps in Healthcare: A Scoping Review of Transfer Learning in Biomedical Data Analysis. CoRR abs/2407.11034 (2024) - 2023
- [j10]Mingxuan Liu, Siqi Li, Han Yuan, Marcus Eng Hock Ong, Yilin Ning, Feng Xie, Seyed Ehsan Saffari, Yuqing Shang, Victor Volovici, Bibhas Chakraborty, Nan Liu:
Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques. Artif. Intell. Medicine 142: 102587 (2023) - [j9]Siqi Li, Pinyan Liu, Gustavo G. Nascimento, Xinru Wang, Fabio Renato Manzolli Leite, Bibhas Chakraborty, Chuan Hong, Yilin Ning, Feng Xie, Zhen Ling Teo, Daniel Shu Wei Ting, Hamed Haddadi, Marcus Eng Hock Ong, Marco Aurélio Peres, Nan Liu:
Federated and distributed learning applications for electronic health records and structured medical data: a scoping review. J. Am. Medical Informatics Assoc. 30(12): 2041-2049 (2023) - [j8]Siqi Li, Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Chuan Hong, Feng Xie, Han Yuan, Mingxuan Liu, Daniel M. Buckland, Yong Chen, Nan Liu:
FedScore: A privacy-preserving framework for federated scoring system development. J. Biomed. Informatics 146: 104485 (2023) - [j7]Mingxuan Liu, Yilin Ning, Salinelat Teixayavong, Mayli Mertens, Jie Xu, Daniel Shu Wei Ting, Lionel Tim-Ee Cheng, Jasmine Chiat Ling Ong, Zhen Ling Teo, Ting Fang Tan, Ravi Chandran Narrendar, Fei Wang, Leo Anthony Celi, Marcus Eng Hock Ong, Nan Liu:
A translational perspective towards clinical AI fairness. npj Digit. Medicine 6 (2023) - [i15]Siqi Li, Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Chuan Hong, Feng Xie, Han Yuan, Mingxuan Liu, Daniel M. Buckland, Yong Chen, Nan Liu:
FedScore: A privacy-preserving framework for federated scoring system development. CoRR abs/2303.00282 (2023) - [i14]Yilin Ning, Victor Volovici, Marcus Eng Hock Ong, Benjamin Alan Goldstein, Nan Liu:
A roadmap to fair and trustworthy prediction model validation in healthcare. CoRR abs/2304.03779 (2023) - [i13]Siqi Li, Pinyan Liu, Gustavo G. Nascimento, Xinru Wang, Fabio Renato Manzolli Leite, Bibhas Chakraborty, Chuan Hong, Yilin Ning, Feng Xie, Zhen Ling Teo, Daniel Shu Wei Ting, Hamed Haddadi, Marcus Eng Hock Ong, Marco Aurélio Peres, Nan Liu:
Federated and distributed learning applications for electronic health records and structured medical data: A scoping review. CoRR abs/2304.07310 (2023) - [i12]Mingxuan Liu, Yilin Ning, Salinelat Teixayavong, Mayli Mertens, Jie Xu, Daniel Shu Wei Ting, Lionel Tim-Ee Cheng, Jasmine Chiat Ling Ong, Zhen Ling Teo, Ting Fang Tan, Ravi Chandran Narrendar, Fei Wang, Leo Anthony Celi, Marcus Eng Hock Ong, Nan Liu:
Towards clinical AI fairness: A translational perspective. CoRR abs/2304.13493 (2023) - [i11]Yilin Ning, Salinelat Teixayavong, Yuqing Shang, Julian Savulescu, Vaishaanth Nagaraj, Di Miao, Mayli Mertens, Daniel Shu Wei Ting, Jasmine Chiat Ling Ong, Mingxuan Liu, Jiuwen Cao, Michael Dunn, Roger Vaughan, Marcus Eng Hock Ong, Joseph Jao-Yiu Sung, Eric J. Topol, Nan Liu:
Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist. CoRR abs/2311.02107 (2023) - [i10]Siqi Li, Di Miao, Qiming Wu, Chuan Hong, Danny D'Agostino, Xin Li, Yilin Ning, Yuqing Shang, Huazhu Fu, Marcus Eng Hock Ong, Hamed Haddadi, Nan Liu:
Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches. CoRR abs/2311.03417 (2023) - 2022
- [j6]Feng Xie, Yilin Ning, Han Yuan, Benjamin Alan Goldstein, Marcus Eng Hock Ong, Nan Liu, Bibhas Chakraborty:
AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data. J. Biomed. Informatics 125: 103959 (2022) - [j5]Feng Xie, Han Yuan, Yilin Ning, Marcus Eng Hock Ong, Mengling Feng, Wynne Hsu, Bibhas Chakraborty, Nan Liu:
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies. J. Biomed. Informatics 126: 103980 (2022) - [j4]Han Yuan, Feng Xie, Marcus Eng Hock Ong, Yilin Ning, Marcel Lucas Chee, Seyed Ehsan Saffari, Hairil Rizal Abdullah, Benjamin Alan Goldstein, Bibhas Chakraborty, Nan Liu:
AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data. J. Biomed. Informatics 129: 104072 (2022) - [j3]Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Benjamin Alan Goldstein, Daniel Shu Wei Ting, Roger Vaughan, Nan Liu:
Shapley variable importance cloud for interpretable machine learning. Patterns 3(4): 100452 (2022) - [j2]Yun Ke, Enzhe Song, Yanzhen Chen, Chong Yao, Yilin Ning:
Multiscale Bidirectional Diversity Entropy for Diesel Injector Fault-Type Diagnosis and Fault Degree Diagnosis. IEEE Trans. Instrum. Meas. 71: 1-10 (2022) - [c4]Yilin Ning, Siqi Li, Marcus Eng Hock Ong, Feng Xie, Bibhas Chakraborty, Daniel Shu Wei Ting, Nan Liu:
A Novel Interpretable Machine Learning System to Generate Clinical Risk Scores: An Application for Predicting Early Mortality or Unplanned Readmission in A Retrospective Cohort Study. AMIA 2022 - [c3]Seyed Ehsan Saffari, Yilin Ning, Feng Xie, Bibhas Chakraborty, Victor Volovici, Roger Vaughan, Marcus Eng Hock Ong, Nan Liu:
AutoScore-Ordinal: An Interpretable Machine Learning Framework for Generating Scoring Models for Ordinal Outcomes. AMIA 2022 - [i9]Yilin Ning, Siqi Li, Marcus Eng Hock Ong, Feng Xie, Bibhas Chakraborty, Daniel Shu Wei Ting, Nan Liu:
A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study. CoRR abs/2201.03291 (2022) - [i8]Seyed Ehsan Saffari, Yilin Ning, Feng Xie, Bibhas Chakraborty, Victor Volovici, Roger Vaughan, Marcus Eng Hock Ong, Nan Liu:
AutoScore-Ordinal: An interpretable machine learning framework for generating scoring models for ordinal outcomes. CoRR abs/2202.08407 (2022) - [i7]Mingxuan Liu, Yilin Ning, Han Yuan, Marcus Eng Hock Ong, Nan Liu:
Balanced background and explanation data are needed in explaining deep learning models with SHAP: An empirical study on clinical decision making. CoRR abs/2206.04050 (2022) - [i6]Mingxuan Liu, Siqi Li, Han Yuan, Marcus Eng Hock Ong, Yilin Ning, Feng Xie, Seyed Ehsan Saffari, Victor Volovici, Bibhas Chakraborty, Nan Liu:
Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques. CoRR abs/2210.08258 (2022) - [i5]Yilin Ning, Mingxuan Liu, Nan Liu:
Shapley variable importance cloud for machine learning models. CoRR abs/2212.08370 (2022) - 2021
- [i4]Feng Xie, Yilin Ning, Han Yuan, Benjamin Alan Goldstein, Marcus Eng Hock Ong, Nan Liu, Bibhas Chakraborty:
AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data. CoRR abs/2106.06957 (2021) - [i3]Han Yuan, Feng Xie, Marcus Eng Hock Ong, Yilin Ning, Marcel Lucas Chee, Seyed Ehsan Saffari, Hairil Rizal Abdullah, Benjamin Alan Goldstein, Bibhas Chakraborty, Nan Liu:
AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data. CoRR abs/2107.06039 (2021) - [i2]Feng Xie, Han Yuan, Yilin Ning, Marcus Eng Hock Ong, Mengling Feng, Wynne Hsu, Bibhas Chakraborty, Nan Liu:
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies. CoRR abs/2107.09951 (2021) - [i1]Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Benjamin Alan Goldstein, Daniel Shu Wei Ting, Roger Vaughan, Nan Liu:
Shapley variable importance clouds for interpretable machine learning. CoRR abs/2110.02484 (2021)
2010 – 2019
- 2019
- [c2]Jinwei Cai, Yilin Ning, Wenshi Li, Linhong Yao:
Research on Anti-Noise Performance of New Chaos Criterion. DSA 2019: 503-504 - 2018
- [j1]Ying Chen, Shih Ling Kao, Maudrene Tan, Yilin Ning, Mark Kevin Salloway, Wee Hwee Lin, Kavita Venkataraman, Eric Khoo Yin Hao, Yeow Leng Chow, E. Shyong Tai, Chuen Seng Tan:
Feasibility of representing adherence to blood glucose monitoring through visualizations: A pilot survey study among healthcare workers. Int. J. Medical Informatics 120: 172-178 (2018) - 2016
- [c1]Mark Kevin Salloway, Xiaodong Deng, Yilin Ning, Shih Ling Kao, Ying Chen, G. Owen Schaefer, Jacqueline Joon-Lin Chin, E. Shyong Tai, Chuen Seng Tan:
A de-identification tool for users in medical operations and public health. BHI 2016: 529-532
Coauthor Index
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last updated on 2024-10-18 19:29 CEST by the dblp team
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