Marcus Eng Hock Ong

Orcid: 0000-0001-7874-7612

According to our database1, Marcus Eng Hock Ong authored at least 54 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
FAIM: Fairness-aware interpretable modeling for trustworthy machine learning in healthcare.
Patterns, 2024

Towards Clinical AI Fairness: Filling Gaps in the Puzzle.
CoRR, 2024

Survival modeling using deep learning, machine learning and statistical methods: A comparative analysis for predicting mortality after hospital admission.
CoRR, 2024

Fairness-Aware Interpretable Modeling (FAIM) for Trustworthy Machine Learning in Healthcare.
CoRR, 2024

Developing Federated Time-to-Event Scores Using Heterogeneous Real-World Survival Data.
CoRR, 2024

2023
Federated and distributed learning applications for electronic health records and structured medical data: a scoping review.
J. Am. Medical Informatics Assoc., November, 2023

FedScore: A privacy-preserving framework for federated scoring system development.
J. Biomed. Informatics, October, 2023

Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques.
Artif. Intell. Medicine, August, 2023

HRnV-Calc: A Software for Heart Rate n-Variability and Heart Rate Variability Analysis.
J. Open Source Softw., July, 2023

Viewing the Role of Alternate Care Service Pathways in the Emergency Care System through a Causal Loop Diagram Lens.
Syst., May, 2023

A translational perspective towards clinical AI fairness.
npj Digit. Medicine, 2023

Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches.
CoRR, 2023

Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist.
CoRR, 2023

Towards clinical AI fairness: A translational perspective.
CoRR, 2023

A roadmap to fair and trustworthy prediction model validation in healthcare.
CoRR, 2023

2022
Shapley variable importance cloud for interpretable machine learning.
Patterns, 2022

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data.
J. Biomed. Informatics, 2022

Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies.
J. Biomed. Informatics, 2022

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.
J. Biomed. Informatics, 2022

Resuming elective surgery after COVID-19: A simulation modelling framework for guiding the phased opening of operating rooms.
Int. J. Medical Informatics, 2022

Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques.
CoRR, 2022

Balanced background and explanation data are needed in explaining deep learning models with SHAP: An empirical study on clinical decision making.
CoRR, 2022

Simulation-Based Analysis of Evacuation Elevator Allocation for a Multi-Level Hospital Emergency Department.
Proceedings of the Winter Simulation Conference, 2022

Benchmarking Emergency Department Triage Prediction Models with Machine Learning and Large Public Electronic Health Records.
Proceedings of the AMIA 2022, 2022

AutoScore-Ordinal: An Interpretable Machine Learning Framework for Generating Scoring Models for Ordinal Outcomes.
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.
Proceedings of the AMIA 2022, 2022

2021
Benchmarking Predictive Risk Models for Emergency Departments with Large Public Electronic Health Records.
CoRR, 2021

HRnV-Calc: A software package for heart rate n-variability and heart rate variability analysis.
CoRR, 2021

Shapley variable importance clouds for interpretable machine learning.
CoRR, 2021

A Model-based Analysis of Evacuation Strategies in Hospital Emergency Departments.
Proceedings of the Winter Simulation Conference, 2021

Recurrent Temporal Point Process Network for First and Repeated Clinical Events.
Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

Development and Validation of a Survival Score for the Emergency Department in Singapore.
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.
Proceedings of the Digital Personalized Health and Medicine - Proceedings of MIE 2020, Medical Informatics Europe, Geneva, Switzerland, April 28, 2020

Modeling Helping Behavior in Emergency Evacuations Using Volunteer's Dilemma Game.
Proceedings of the Computational Science - ICCS 2020, 2020

Risk-Based AED Placement - Singapore Case.
Proceedings of the Computational Science - ICCS 2020, 2020

2019
A Novel Picture Fingerprinting Technique to Provide Practical Indoor Localization for Wheelchair Users.
Proceedings of the HCI International 2019 - Posters - 21st International Conference, 2019

Explainable AI: Classification of MRI Brain Scans Orders for Quality Improvement.
Proceedings of the 6th IEEE/ACM International Conference on Big Data Computing, 2019

Serial Heart Rate Variability Measures for Risk Prediction of Septic Patients in the Emergency Department.
Proceedings of the AMIA 2019, 2019

2018
A Novel Approach for Assessing Power Wheelchair Users' Mobility by Using Curve Fitting.
Proceedings of the Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management, 2018

Predictive Modeling of Hospital Readmissions with Sparse Bayesian Extreme Learning Machine.
Proceedings of ELM 2018, 2018

2017
FAM-FACE-SG: a score for risk stratification of frequent hospital admitters.
BMC Medical Informatics Decis. Mak., 2017

Simulation-based decision support framework for dynamic ambulance redeployment in Singapore.
Int. J. Medical Informatics, 2017

Ensemble-Based Risk Scoring with Extreme Learning Machine for Prediction of Adverse Cardiac Events.
Cogn. Comput., 2017

A Feasible and Terrain-Insensitive Approach for Analyzing Power Wheelchair Users' Mobility.
Proceedings of the 29th IEEE International Conference on Tools with Artificial Intelligence, 2017

2015
Landmark recognition with sparse representation classification and extreme learning machine.
J. Frankl. Inst., 2015

Manifold ranking based scoring system with its application to cardiac arrest prediction: A retrospective study in emergency department patients.
Comput. Biol. Medicine, 2015

Multi-objective optimization for a hospital inpatient flow process via discrete event simulation.
Proceedings of the 2015 Winter Simulation Conference, 2015

Effects of two new features of approximate entropy and sample entropy on cardiac arrest prediction.
Proceedings of the 2015 IEEE International Symposium on Circuits and Systems, 2015

Analysis of patient outcome using ECG and extreme learning machine ensemble.
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.
IEEE J. Biomed. Health Informatics, 2014

Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection.
BMC Medical Informatics Decis. Mak., 2014

2012
An Intelligent Scoring System and Its Application to Cardiac Arrest Prediction.
IEEE Trans. Inf. Technol. Biomed., 2012

2011
Patient Outcome Prediction with Heart Rate Variability and Vital Signs.
J. Signal Process. Syst., 2011

2008
Patient classification based on pre-hospital heart rate variability.
Proceedings of the IEEE Asia Pacific Conference on Circuits and Systems, 2008


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