Aaron J. Peace
Orcid: 0000-0001-9556-7509
According to our database1,
Aaron J. Peace
authored at least 16 papers
between 2015 and 2022.
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Bibliography
2022
Machine learning and the electrocardiogram over two decades: Time series and meta-analysis of the algorithms, evaluation metrics and applications.
Artif. Intell. Medicine, 2022
2020
Computational time series analysis of patient referrals to a primary percutaneous coronary intervention service.
Health Informatics J., 2020
Improving the Detection of Acute Coronary Syndrome Using Machine Learning of Blood Biomarkers.
Proceedings of the Computing in Cardiology, 2020
Machine Learning to Predict 30 Days and 1-Year Mortality in STEMI and Turndown Patients.
Proceedings of the Computing in Cardiology, 2020
Towards Explainable Artificial Intelligence and Explanation User Interfaces to Open the 'Black Box' of Automated ECG Interpretation.
Proceedings of the Advanced Visual Interfaces. Supporting Artificial Intelligence and Big Data Applications, 2020
2019
Wearable technology-based metrics for predicting operator performance during cardiac catheterisation.
Int. J. Comput. Assist. Radiol. Surg., 2019
Proceedings of the 31st European Conference on Cognitive Ergonomics, 2019
Role of dashboards in improving decision making in healthcare: Review of the literature.
Proceedings of the 31st European Conference on Cognitive Ergonomics, 2019
Machine Learning Improves the Detection of Misplaced V1 and V2 Electrodes During 12-Lead Electrocardiogram Acquisition.
Proceedings of the 46th Computing in Cardiology, 2019
Unsupervised Machine Learning Elicits Patient Archetypes in a Primary Percutaneous Coronary Intervention Service.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
Predicting 30 days Mortality in STEMI Patients using Patient Referral Data to a Primary Percutaneous Coronary Intervention Service.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
2018
Eye Tracking the Visual Attention of Nurses Interpreting Simulated Vital Signs Scenarios: Mining Metrics to Discriminate Between Performance Level.
IEEE Trans. Hum. Mach. Syst., 2018
2017
Parsing HL7 aECG Files and Segmenting Leads for Interactive Progressive-based Interpretation of the 12-Lead Electrocardiogram.
Proceedings of the Computing in Cardiology, 2017
2016
A computer-human interaction model to improve the diagnostic accuracy and clinical decision-making during 12-lead electrocardiogram interpretation.
J. Biomed. Informatics, 2016
An Eye-Tracking Assessment of Coronary Care Nurses during the Interpretation of Patient Monitoring Scenarios.
Proceedings of the Computing in Cardiology, CinC 2016, Vancouver, 2016
2015
Interactive Progressive-based Approach to Aid the Human Interpretation of the 12-lead Electrocardiogram.
Proceedings of the Computing in Cardiology, 2015