Leveraging Neural-Networks, Boosting and Domain-Knowledge to Discover Physiological Indicators with Minimal Sensitivity to Data Resolution-Reference-Cited by-同舟云学术

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Leveraging Neural-Networks, Boosting and Domain-Knowledge to Discover Physiological Indicators with Minimal Sensitivity to Data Resolution

Published:2022-08-19 Issue: Volume: Page:
ISSN:
Container-title:2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)
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Author:

Vartanov Dmitrii¹,Senyukova Olga¹,Miao Rebecca²,Orlova Marina²,Yang Zhenyi²,Gavrishchaka Valeriy³

Affiliation:

1. Lomonosov Moscow State University,Moscow,Russian Federation

2. Applied Quantitative Solutions for Complex Systems,Falls Church,VA,USA

3. West Virginia University,Physics Department,Morgantown,WV,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9904023/9904007/09904143.pdf?arnumber=9904143

Reference24 articles.

1. XGBoost

2. Discovery of early-alert indicators using hybrid ensemble learning and generative physics-based models

3. Model for complex heart rate dynamics in health and diseases

4. Bifurcations in a nonlinear model of the baroreceptor-cardiac reflex

5. Methods derived from nonlinear dynamics for analysing heart rate variability

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Medical-informed machine learning: integrating prior knowledge into medical decision systems;BMC Medical Informatics and Decision Making;2024-06-28

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