Mingxuan Liu - RankMe

21 papers Journal 20Unranked 1

Year	Rank	Type	Title / Venue / Authors
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`	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`	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`	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 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`	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	—	`conf`	Interpretable Machine Learning-Based Risk Scoring with Individual and Ensemble Model Selection for Clinical Decision Making. Tiny Papers @ ICLR Han Yuan, Jin Wee Lee, Mingxuan Liu, Siqi Li, Chenglin Niu, Jun Wen, Feng Xie
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	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`	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`	Shapley variable importance cloud for machine learning models. CoRR Yilin Ning, Mingxuan Liu, Nan Liu