Yilin Ning - RankMe

47 papers Misc 2Journal 42Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Toward Global Large Language Models in Medicine. CoRR Rui Yang, Huitao Li, Weihao Xuan, Heli Qi, Xin Li, Kunyu Yu, Yingjian Chen, Rongrong Wang, Jacques Behmoaras, Tianxi Cai, Bibhas Chakraborty, Qingyu Chen, Lionel Tim-Ee Cheng, Marie-Louise Damwanza, Chido Dzinotyiwei, Aosong Feng, Chuan Hong, Yusuke Iwasawa, Yuhe Ke, Linah Kitala, Taehoon Ko, Jisan Lee, Irene Li, Jonathan Chong Kai Liew, Hongfang Liu, Lian Leng Low, Edison Marrese-Taylor, Yutaka Matsuo, Isheanesu Misi, Yilin Ning, Jasmine Chiat Ling Ong, Marcus Eng Hock Ong, Enrico Petretto, Hossein Rouhizadeh, Abiram Sandralegar, Oren Schreier, Iain Bee Huat Tan, Patrick Tan, Daniel Shu Wei Ting, Junjue Wang, Chunhua Weng, Matthew Yu Heng Wong, Fang Wu, Yunze Xiao, Xuhai Xu, Qingcheng Zeng, Zhuo Zheng, Yifan Peng, Douglas Teodoro, Nan Liu
2025	J	`jnl`	A scoping review and evidence gap analysis of clinical AI fairness. npj Digit. Medicine Mingxuan Liu, Yilin Ning, Salinelat Teixayavong, Xiaoxuan Liu, Mayli Mertens, Yuqing Shang, Xin Li, Di Miao, Jingchi Liao, 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
2025	J	`jnl`	Developing federated time-to-event scores using heterogeneous real-world survival data. Comput. Biol. Medicine Siqi Li, Ziwen Wang, Yuqing Shang, Qiming Wu, Chuan Hong, Yilin Ning, Di Miao, Marcus Eng Hock Ong, Bibhas Chakraborty, Nan Liu
2025	J	`jnl`	Equitable Survival Prediction: A Fairness-Aware Survival Modeling (FASM) Approach. CoRR Mingxuan Liu, Yilin Ning, Haoyuan Wang, Chuan Hong, Matthew Engelhard, Danielle S. Bitterman, William G. La Cava, Nan Liu
2025	—	`conf`	FairFML: A Unified Approach to Algorithmic Fair Federated Learning with Applications to Reducing Gender Disparities in Cardiac Arrest Outcomes. MedInfo Siqi Li, Qiming Wu, Xin Li, Di Miao, Chuan Hong, Wenjun Gu, Yilin Ning, Yuqing Shang, Nan Liu
2025	J	`jnl`	Gender Bias in Large Language Models for Healthcare: Assignment Consistency and Clinical Implications. CoRR Mingxuan Liu, Yuhe Ke, Wentao Zhu, Mayli Mertens, Yilin Ning, Jingchi Liao, Chuan Hong, Daniel Shu Wei Ting, Yifan Peng, Danielle S. Bitterman, Marcus Eng Hock Ong, Nan Liu
2025	J	`jnl`	Regulatory Science Innovation for Generative AI and Large Language Models in Health and Medicine: A Global Call for Action. CoRR Jasmine Chiat Ling Ong, Yilin Ning, Mingxuan Liu, Yian Ma, Zhao Liang, Kuldev Singh, Robert T. Chang, Silke Vogel, John CW Lim, Iris Siu Kwan Tan, Oscar Freyer, Stephen Gilbert, Danielle S. Bitterman, Xiaoxuan Liu, Alastair K. Denniston, Nan Liu
2025	J	`jnl`	seeBias: A Comprehensive Tool for Assessing and Visualizing AI Fairness. CoRR Yilin Ning, Yian Ma, Mingxuan Liu, Xin Li, Nan Liu
2025	J	`jnl`	⁠Advancing ethical AI in healthcare through interpretability. Patterns Yilin Ning, Mingxuan Liu, Nan Liu
2024	J	`jnl`	Bridging Data Gaps in Healthcare: A Scoping Review of Transfer Learning in Biomedical Data Analysis. CoRR 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
2024	J	`jnl`	Developing Federated Time-to-Event Scores Using Heterogeneous Real-World Survival Data. CoRR Siqi Li, Yuqing Shang, Ziwen Wang, Qiming Wu, Chuan Hong, Yilin Ning, Di Miao, Marcus Eng Hock Ong, Bibhas Chakraborty, Nan Liu
2024	J	`jnl`	Disparities in clinical studies of AI enabled applications from a global perspective. npj Digit. Medicine Rui Yang, Sabarinath Vinod Nair, Yuhe Ke, Danny D'Agostino, Mingxuan Liu, Yilin Ning, Nan Liu
2024	J	`jnl`	FAIM: Fairness-aware interpretable modeling for trustworthy machine learning in healthcare. Patterns Mingxuan Liu, Yilin Ning, Yuhe Ke, Yuqing Shang, Bibhas Chakraborty, Marcus Eng Hock Ong, Roger Vaughan, Nan Liu
2024	J	`jnl`	FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome Prediction. CoRR Siqi Li, Qiming Wu, Xin Li, Di Miao, Chuan Hong, Wenjun Gu, Yuqing Shang, Yohei Okada, Michael Hao Chen, Mengying Yan, Yilin Ning, Marcus Eng Hock Ong, Nan Liu
2024	J	`jnl`	Fairness-Aware Interpretable Modeling (FAIM) for Trustworthy Machine Learning in Healthcare. CoRR Mingxuan Liu, Yilin Ning, Yuhe Ke, Yuqing Shang, Bibhas Chakraborty, Marcus Eng Hock Ong, Roger Vaughan, Nan Liu
2024	J	`jnl`	Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine. CoRR Rui Yang, Yilin Ning, Emilia Keppo, Mingxuan Liu, Chuan Hong, Danielle S. Bitterman, Jasmine Chiat Ling Ong, Daniel Shu Wei Ting, Nan Liu
2024	J	`jnl`	Survival modeling using deep learning, machine learning and statistical methods: A comparative analysis for predicting mortality after hospital admission. CoRR Ziwen Wang, Jin Wee Lee, Tanujit Chakraborty, Yilin Ning, Mingxuan Liu, Feng Xie, Marcus Eng Hock Ong, Nan Liu
2024	J	`jnl`	Towards Clinical AI Fairness: Filling Gaps in the Puzzle. CoRR 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
2023	J	`jnl`	A roadmap to fair and trustworthy prediction model validation in healthcare. CoRR Yilin Ning, Victor Volovici, Marcus Eng Hock Ong, Benjamin Alan Goldstein, Nan Liu
2023	J	`jnl`	A translational perspective towards clinical AI fairness. npj Digit. Medicine 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
2023	J	`jnl`	FedScore: A privacy-preserving framework for federated scoring system development. CoRR 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
2023	J	`jnl`	FedScore: A privacy-preserving framework for federated scoring system development. J. Biomed. Informatics 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
2023	J	`jnl`	Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches. CoRR 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
2023	J	`jnl`	Federated and distributed learning applications for electronic health records and structured medical data: A scoping review. CoRR 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
2023	J	`jnl`	Federated and distributed learning applications for electronic health records and structured medical data: a scoping review. J. Am. Medical Informatics Assoc. 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
2023	J	`jnl`	Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist. CoRR 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
2023	J	`jnl`	Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques. Artif. Intell. Medicine 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
2023	J	`jnl`	Towards clinical AI fairness: A translational perspective. CoRR 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
2022	Misc	`conf`	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 Yilin Ning, Siqi Li, Marcus Eng Hock Ong, Feng Xie, Bibhas Chakraborty, Daniel Shu Wei Ting, Nan Liu
2022	J	`jnl`	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 Yilin Ning, Siqi Li, Marcus Eng Hock Ong, Feng Xie, Bibhas Chakraborty, Daniel Shu Wei Ting, Nan Liu
2022	J	`jnl`	AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data. J. Biomed. Informatics 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
2022	Misc	`conf`	AutoScore-Ordinal: An Interpretable Machine Learning Framework for Generating Scoring Models for Ordinal Outcomes. AMIA Seyed Ehsan Saffari, Yilin Ning, Feng Xie, Bibhas Chakraborty, Victor Volovici, Roger Vaughan, Marcus Eng Hock Ong, Nan Liu
2022	J	`jnl`	AutoScore-Ordinal: An interpretable machine learning framework for generating scoring models for ordinal outcomes. CoRR Seyed Ehsan Saffari, Yilin Ning, Feng Xie, Bibhas Chakraborty, Victor Volovici, Roger Vaughan, Marcus Eng Hock Ong, Nan Liu
2022	J	`jnl`	AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data. J. Biomed. Informatics Feng Xie, Yilin Ning, Han Yuan, Benjamin Alan Goldstein, Marcus Eng Hock Ong, Nan Liu, Bibhas Chakraborty
2022	J	`jnl`	Balanced background and explanation data are needed in explaining deep learning models with SHAP: An empirical study on clinical decision making. CoRR Mingxuan Liu, Yilin Ning, Han Yuan, Marcus Eng Hock Ong, Nan Liu
2022	J	`jnl`	Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies. J. Biomed. Informatics Feng Xie, Han Yuan, Yilin Ning, Marcus Eng Hock Ong, Mengling Feng, Wynne Hsu, Bibhas Chakraborty, Nan Liu
2022	J	`jnl`	Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques. CoRR Mingxuan Liu, Siqi Li, Han Yuan, Marcus Eng Hock Ong, Yilin Ning, Feng Xie, Seyed Ehsan Saffari, Victor Volovici, Bibhas Chakraborty, Nan Liu
2022	J	`jnl`	Multiscale Bidirectional Diversity Entropy for Diesel Injector Fault-Type Diagnosis and Fault Degree Diagnosis. IEEE Trans. Instrum. Meas. Yun Ke, Enzhe Song, Yanzhen Chen, Chong Yao, Yilin Ning
2022	J	`jnl`	Shapley variable importance cloud for interpretable machine learning. Patterns Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Benjamin Alan Goldstein, Daniel Shu Wei Ting, Roger Vaughan, Nan Liu
2022	J	`jnl`	Shapley variable importance cloud for machine learning models. CoRR Yilin Ning, Mingxuan Liu, Nan Liu
2021	J	`jnl`	AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data. CoRR 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
2021	J	`jnl`	AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data. CoRR Feng Xie, Yilin Ning, Han Yuan, Benjamin Alan Goldstein, Marcus Eng Hock Ong, Nan Liu, Bibhas Chakraborty
2021	J	`jnl`	Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies. CoRR Feng Xie, Han Yuan, Yilin Ning, Marcus Eng Hock Ong, Mengling Feng, Wynne Hsu, Bibhas Chakraborty, Nan Liu
2021	J	`jnl`	Shapley variable importance clouds for interpretable machine learning. CoRR Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Benjamin Alan Goldstein, Daniel Shu Wei Ting, Roger Vaughan, Nan Liu
2019	—	`conf`	Research on Anti-Noise Performance of New Chaos Criterion. DSA Jinwei Cai, Yilin Ning, Wenshi Li, Linhong Yao
2018	J	`jnl`	Feasibility of representing adherence to blood glucose monitoring through visualizations: A pilot survey study among healthcare workers. Int. J. Medical Informatics 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
2016	—	`conf`	A de-identification tool for users in medical operations and public health. BHI 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