Nan Liu

According to our database, Nan Liu authored at least 71 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

FAIM: Fairness-aware interpretable modeling for trustworthy machine learning in healthcare.

Mingxuan Liu, Yilin Ning, Yuhe Ke, Yuqing Shang, Bibhas Chakraborty, Marcus Eng Hock Ong, Roger Vaughan, Nan Liu

Patterns, 2024

Disparities in clinical studies of AI enabled applications from a global perspective.

Rui Yang, Sabarinath Vinod Nair, Yuhe Ke, Danny D'Agostino, Mingxuan Liu, Yilin Ning, Nan Liu

npj Digit. Medicine, 2024

Clinical domain knowledge-derived template improves post hoc AI explanations in pneumothorax classification.

Han Yuan, Chuan Hong, Pengtao Jiang, Gangming Zhao, Nguyen Tuan Anh Tran, Xinxing Xu, Yet Yen Yan, Nan Liu

J. Biomed. Informatics, 2024

oRetrieval Augmented Generation for 10 Large Language Models and its Generalizability in Assessing Medical Fitness.

Yuhe Ke, Liyuan Jin, Kabilan Elangovan, Hairil Rizal Abdullah, Nan Liu, Alex Tiong Heng Sia, Chai Rick Soh, Joshua Yi Min Tung, Jasmine Chiat Ling Ong, Chang Fu Kuo, Shao-Chun Wu, Vesela P. Kovacheva, Daniel Shu Wei Ting

CoRR, 2024

Lightweight Large Language Model for Medication Enquiry: Med-Pal.

Kabilan Elangovan, Jasmine Chiat Ling Ong, Liyuan Jin, Benjamin Jun Jie Seng, Yu Heng Kwan, Lit Soo Tan, Ryan Jian Zhong, Justina Koi Li Ma, Yuhe Ke, Nan Liu, Kathleen M. Giacomini, Daniel Shu Wei Ting

CoRR, 2024

Bridging Data Gaps in Healthcare: A Scoping Review of Transfer Learning in Biomedical Data Analysis.

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

CoRR, 2024

A Proposed S.C.O.R.E. Evaluation Framework for Large Language Models : Safety, Consensus, Objectivity, Reproducibility and Explainability.

Ting Fang Tan, Kabilan Elangovan, Jasmine Chiat Ling Ong, Nigam Shah, Joseph Jao-Yiu Sung, Tien Yin Wong, Lan Xue, Nan Liu, Haibo Wang, Chang Fu Kuo, Simon Chesterman, Zee Kin Yeong, Daniel S. W. Ting

CoRR, 2024

Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine.

Rui Yang, Yilin Ning, Emilia Keppo, Mingxuan Liu, Chuan Hong, Danielle S. Bitterman, Jasmine Chiat Ling Ong, Daniel Shu Wei Ting, Nan Liu

CoRR, 2024

Towards Clinical AI Fairness: Filling Gaps in the Puzzle.

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

CoRR, 2024

Survival modeling using deep learning, machine learning and statistical methods: A comparative analysis for predicting mortality after hospital admission.

Ziwen Wang, Jin Wee Lee, Tanujit Chakraborty, Yilin Ning, Mingxuan Liu, Feng Xie, Marcus Eng Hock Ong, Nan Liu

CoRR, 2024

Fairness-Aware Interpretable Modeling (FAIM) for Trustworthy Machine Learning in Healthcare.

Mingxuan Liu, Yilin Ning, Yuhe Ke, Yuqing Shang, Bibhas Chakraborty, Marcus Eng Hock Ong, Roger Vaughan, Nan Liu

CoRR, 2024

Developing Federated Time-to-Event Scores Using Heterogeneous Real-World Survival Data.

Siqi Li, Yuqing Shang, Ziwen Wang, Qiming Wu, Chuan Hong, Yilin Ning, Di Miao, Marcus Eng Hock Ong, Bibhas Chakraborty, Nan Liu

CoRR, 2024

Fine-tuning Large Language Model (LLM) Artificial Intelligence Chatbots in Ophthalmology and LLM-based evaluation using GPT-4.

Ting Fang Tan, Kabilan Elangovan, Liyuan Jin, Yao Jie, Li Yong, Joshua Lim, Stanley Poh, Wei Yan Ng, Daniel Yan Zheng Lim, Yuhe Ke, Nan Liu, Daniel Shu Wei Ting

CoRR, 2024

Development and Testing of Retrieval Augmented Generation in Large Language Models - A Case Study Report.

Yuhe Ke, Liyuan Jin, Kabilan Elangovan, Hairil Rizal Abdullah, Nan Liu, Alex Tiong Heng Sia, Chai Rick Soh, Joshua Yi Min Tung, Jasmine Chiat Ling Ong, Daniel Shu Wei Ting

CoRR, 2024

Enhancing Diagnostic Accuracy through Multi-Agent Conversations: Using Large Language Models to Mitigate Cognitive Bias.

Yuhe Ke, Rui Yang, Sui An Lie, Taylor Xin Yi Lim, Hairil Rizal Abdullah, Daniel Shu Wei Ting, Nan Liu

CoRR, 2024

Evaluating the Efficacy of Federated Scoring Systems with Heterogeneous Electronic Health Records.

Qiming Wu, Siqi Li, Di Miao, Yuqing Shang, Xin Li, Nan Liu

Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

2023

Federated and distributed learning applications for electronic health records and structured medical data: a scoping review.

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

J. Am. Medical Informatics Assoc., November, 2023

FedScore: A privacy-preserving framework for federated scoring system development.

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

J. Biomed. Informatics, October, 2023

Epicasting: An Ensemble Wavelet Neural Network for forecasting epidemics.

Madhurima Panja, Tanujit Chakraborty, Uttam Kumar, Nan Liu

Neural Networks, August, 2023

A scoping review of the clinical application of machine learning in data-driven population segmentation analysis.

Pinyan Liu, Ziwen Wang, Nan Liu, Marco Aurélio Peres

J. Am. Medical Informatics Assoc., August, 2023

Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques.

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

Artif. Intell. Medicine, August, 2023

HRnV-Calc: A Software for Heart Rate n-Variability and Heart Rate Variability Analysis.

Chenglin Niu, Dagang Guo, Marcus Eng Hock Ong, Zhixiong Koh, Guerry Alexiane Laure Marie-Alix, Andrew Fu Wah Ho, Zhiping Lin, Chengyu Liu, Gari D. Clifford, Nan Liu

J. Open Source Softw., July, 2023

A translational perspective towards clinical AI fairness.

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

npj Digit. Medicine, 2023

Leveraging Anatomical Constraints with Uncertainty for Pneumothorax Segmentation.

Han Yuan, Chuan Hong, Nguyen Tuan Anh Tran, Xinxing Xu, Nan Liu

CoRR, 2023

Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches.

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

CoRR, 2023

Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist.

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

CoRR, 2023

Towards clinical AI fairness: A translational perspective.

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

CoRR, 2023

A roadmap to fair and trustworthy prediction model validation in healthcare.

Yilin Ning, Victor Volovici, Marcus Eng Hock Ong, Benjamin Alan Goldstein, Nan Liu

CoRR, 2023

2022

Shapley variable importance cloud for interpretable machine learning.

Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Benjamin Alan Goldstein, Daniel Shu Wei Ting, Roger Vaughan, Nan Liu

Patterns, 2022

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data.

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

J. Biomed. Informatics, 2022

Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies.

Feng Xie, Han Yuan, Yilin Ning, Marcus Eng Hock Ong, Mengling Feng, Wynne Hsu, Bibhas Chakraborty, Nan Liu

J. Biomed. Informatics, 2022

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.

Feng Xie, Yilin Ning, Han Yuan, Benjamin Alan Goldstein, Marcus Eng Hock Ong, Nan Liu, Bibhas Chakraborty

J. Biomed. Informatics, 2022

Shapley variable importance cloud for machine learning models.

Yilin Ning, Mingxuan Liu, Nan Liu

CoRR, 2022

Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques.

Mingxuan Liu, Siqi Li, Han Yuan, Marcus Eng Hock Ong, Yilin Ning, Feng Xie, Seyed Ehsan Saffari, Victor Volovici, Bibhas Chakraborty, Nan Liu

CoRR, 2022

Balanced background and explanation data are needed in explaining deep learning models with SHAP: An empirical study on clinical decision making.

Mingxuan Liu, Yilin Ning, Han Yuan, Marcus Eng Hock Ong, Nan Liu

CoRR, 2022

Benchmarking Emergency Department Triage Prediction Models with Machine Learning and Large Public Electronic Health Records.

Feng Xie, Jun Zhou, Jin Wee Lee, Mingrui Tan, Siqi Li, Logasan S/O Rajnthern, Marcel Lucas Chee, Bibhas Chakraborty, An-Kwok Ian Wong, Alon Dagan, Marcus Eng Hock Ong, Fei Gao, Nan Liu

Proceedings of the AMIA 2022, 2022

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

Seyed Ehsan Saffari, Yilin Ning, Feng Xie, Bibhas Chakraborty, Victor Volovici, Roger Vaughan, Marcus Eng Hock Ong, Nan Liu

Proceedings of the AMIA 2022, 2022

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.

Yilin Ning, Siqi Li, Marcus Eng Hock Ong, Feng Xie, Bibhas Chakraborty, Daniel Shu Wei Ting, Nan Liu

Proceedings of the AMIA 2022, 2022

2021

Benchmarking Predictive Risk Models for Emergency Departments with Large Public Electronic Health Records.

Feng Xie, Jun Zhou, Jin Wee Lee, Mingrui Tan, Siqi Li, Logasan S/O Rajnthern, Marcel Lucas Chee, Bibhas Chakraborty, An-Kwok Ian Wong, Alon Dagan, Marcus Eng Hock Ong, Fei Gao, Nan Liu

CoRR, 2021

HRnV-Calc: A software package for heart rate n-variability and heart rate variability analysis.

Chenglin Niu, Dagang Guo, Marcus Eng Hock Ong, Zhixiong Koh, Andrew Fu Wah Ho, Zhiping Lin, Chengyu Liu, Gari D. Clifford, Nan Liu

CoRR, 2021

Shapley variable importance clouds for interpretable machine learning.

Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Benjamin Alan Goldstein, Daniel Shu Wei Ting, Roger Vaughan, Nan Liu

CoRR, 2021

Development and Validation of a Survival Score for the Emergency Department in Singapore.

Feng Xie, Bibhas Chakraborty, Nan Liu, Marcus Eng Hock Ong

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020

Prediction of ROSC After Cardiac Arrest Using Machine Learning.

Nan Liu, Andrew Fu Wah Ho, Pin Pin Pek, Tsung-Chien Lu, Pairoj Khruekarnchana, Kyoung Jun Song, Hideharu Tanaka, Ghulam Yasin Naroo, Han Nee Gan, Zhixiong Koh, Huei-Ming Ma, Marcus Eng Hock Ong

Proceedings of the Digital Personalized Health and Medicine - Proceedings of MIE 2020, Medical Informatics Europe, Geneva, Switzerland, April 28, 2020

2019

Serial Heart Rate Variability Measures for Risk Prediction of Septic Patients in the Emergency Department.

Calvin Chiew, Han Wang, Marcus Eng Hock Ong, Ting Hway Wong, Zhixiong Koh, Nan Liu, Mengling Feng

Proceedings of the AMIA 2019, 2019

2018

Predictive Modeling of Hospital Readmissions with Sparse Bayesian Extreme Learning Machine.

Nan Liu, Lian Leng Low, Sean Shao Wei Lam, Julian Thumboo, Marcus Eng Hock Ong

Proceedings of ELM 2018, 2018

Development of a Radiology Decision Support System for the Classification of MRI Brain Scans.

Alwin Yaoxian Zhang, Sean Shao Wei Lam, Nan Liu, Yan Pang, Ling Ling Chan, Phua Hwee Tang

Proceedings of the 5th IEEE/ACM International Conference on Big Data Computing Applications and Technologies, 2018

2017

FAM-FACE-SG: a score for risk stratification of frequent hospital admitters.

Lian Leng Low, Nan Liu, Kheng Hock Lee, Marcus Eng Hock Ong, Sijia Wang, Xuan Jing, Julian Thumboo

BMC Medical Informatics Decis. Mak., 2017

Extreme learning machine based mutual information estimation with application to time-series change-points detection.

Beom-Seok Oh, Lei Sun, Chung Soo Ahn, Yong Kiang Yeo, Yan Yang, Nan Liu, Zhiping Lin

Neurocomputing, 2017

Ensemble-Based Risk Scoring with Extreme Learning Machine for Prediction of Adverse Cardiac Events.

Nan Liu, Jeffrey Tadashi Sakamoto, Jiuwen Cao, Zhixiong Koh, Andrew Fu Wah Ho, Zhiping Lin, Marcus Eng Hock Ong

Cogn. Comput., 2017

2015

Landmark recognition with sparse representation classification and extreme learning machine.

Jiuwen Cao, Yanfei Zhao, Xiaoping Lai, Marcus Eng Hock Ong, Chun Yin, Zhixiong Koh, Nan Liu

J. Frankl. Inst., 2015

Ensemble of subset online sequential extreme learning machine for class imbalance and concept drift.

Bilal Mirza, Zhiping Lin, Nan Liu

Neurocomputing, 2015

Manifold ranking based scoring system with its application to cardiac arrest prediction: A retrospective study in emergency department patients.

Tianchi Liu, Zhiping Lin, Marcus Eng Hock Ong, Zhixiong Koh, Pin Pin Pek, Yong Kiang Yeo, Beom-Seok Oh, Andrew Fu Wah Ho, Nan Liu

Comput. Biol. Medicine, 2015

Effects of two new features of approximate entropy and sample entropy on cardiac arrest prediction.

Yumeng Gao, Zhiping Lin, Tongtong Zhang, Nan Liu, Tianchi Liu, Wee Ser, Zhixiong Koh, Marcus Eng Hock Ong

Proceedings of the 2015 IEEE International Symposium on Circuits and Systems, 2015

Analysis of patient outcome using ECG and extreme learning machine ensemble.

Nan Liu, Jiuwen Cao, Zhixiong Koh, Zhiping Lin, Marcus Eng Hock Ong

Proceedings of the 2015 IEEE International Conference on Digital Signal Processing, 2015

Landmark recognition via sparse representation.

Jiuwen Cao, Yanfei Zhao, Xiaoping Lai, Tao Chen, Nan Liu, Bilal Mirza, Zhiping Lin

Proceedings of the 2015 IEEE International Conference on Digital Signal Processing, 2015

2014

Risk Scoring for Prediction of Acute Cardiac Complications from Imbalanced Clinical Data.

Nan Liu, Zhixiong Koh, Eric Chern-Pin Chua, Licia Mei-Ling Tan, Zhiping Lin, Bilal Mirza, Marcus Eng Hock Ong

IEEE J. Biomed. Health Informatics, 2014

Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection.

Nan Liu, Zhi Koh, Junyang Goh, Zhiping Lin, Benjamin Haaland, Boon Ting, Marcus Eng Hock Ong

BMC Medical Informatics Decis. Mak., 2014

2013

Evolutionary Extreme Learning Machine and Its Application to Image Analysis.

Nan Liu, Han Wang

J. Signal Process. Syst., 2013

2012

An Intelligent Scoring System and Its Application to Cardiac Arrest Prediction.

Nan Liu, Zhiping Lin, Jiuwen Cao, Zhixiong Koh, Tongtong Zhang, Guang-Bin Huang, Wee Ser, Marcus Eng Hock Ong

IEEE Trans. Inf. Technol. Biomed., 2012

Voting based extreme learning machine.

Jiuwen Cao, Zhiping Lin, Guang-Bin Huang, Nan Liu

Inf. Sci., 2012

Weighted principal component extraction with genetic algorithms.

Nan Liu, Han Wang

Appl. Soft Comput., 2012

2011

Patient Outcome Prediction with Heart Rate Variability and Vital Signs.

Nan Liu, Zhiping Lin, Zhixiong Koh, Guang-Bin Huang, Wee Ser, Marcus Eng Hock Ong

J. Signal Process. Syst., 2011

2010

Ensemble Based Extreme Learning Machine.

Nan Liu, Han Wang

IEEE Signal Process. Lett., 2010

2009

Modeling Images With Multiple Trace Transforms for Pattern Analysis.

Nan Liu, Han Wang

IEEE Signal Process. Lett., 2009

2008

Improving predictive accuracy by evolving feature selection for face recognition.

Nan Liu, Han Wang

IEICE Electron. Express, 2008

Feature selection in frequency domain and its application to face recognition.

Nan Liu, Han Wang

Proceedings of the International Joint Conference on Neural Networks, 2008

2007

Classification of transformed face images with majority voting.

Nan Liu, Han Wang

Proceedings of the IEEE International Conference on Systems, 2007

Extraction of hybrid trace features with evolutionary computation for face recognition.

Nan Liu, Han Wang

Proceedings of the IEEE Congress on Evolutionary Computation, 2007

2006

Feature Extraction with Genetic Algorithms Based Nonlinear Principal Component Analysis for Face Recognition.

Nan Liu, Han Wang

Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Face Recognition with Weighted Kernel Principal Component Analysis.

Nan Liu, Han Wang, Wei-Yun Yau

Proceedings of the Ninth International Conference on Control, 2006

2005

Feature extraction using evolutionary weighted principal component analysis.

Nan Liu, Han Wang

Proceedings of the IEEE International Conference on Systems, 2005