Biomedical Models
Biomedical Models, Algorithms, and Integrated Quantitative Frameworks
[14] O. Senyukova and V. Gavrishchaka, “Generic Multi-Complexity Representation of Cardiodynamics: From Early Detection of Emerging Abnormalities to Personalized Treatment Optimization”, BIT’s 7th Annual International Congress of Cardiology-2015 (Shanghai, China). � 2015. � P. 176
[13] V.V. Gavrishchaka, O. Senyukova, and K. Davis, “Multi-Complexity Ensemble Measures for Gait Time Series Analysis: Application to Diagnostics, Monitoring and Biometrics”, Book chapter in “Signal and Image Analysis for Biomedical and Life Sciences”, Springer, 2015
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[8] V.V. Gavrishchaka, O.V. Senyukova, M.E. Koepke, and A.I. Kryuchkova, “Multi-objective physiological indicators based on complementary complexity measures: application to early diagnostics and prediction of acute events”, In: International Conference on Computer and Computational Intelligence. Bangkok, Thailand; 2011. p. 95-106
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[7] V.V. Gavrishchaka, O.V. Senyukova, O.N. Ulyanova, and A.G. Monin, “Physiological meta-indicators for professional sports applications: express diagnostics, overtraining detection, and quantification of individual zones of optimal functioning”, In: VII International scientific and practical conference for memory of P.Roudik.; 2011. p. 5-7
EXTENDED ABSTRACT (PDF)
PRESENTATION SLIDES (PDF)
EXTENDED ABSTRACT in RUSSIAN (PDF)
PRESENTATION SLIDES in RUSSIAN (PDF)
[6] O.V. Senyukova, V.V. Gavrishchaka, and Y.M. Bayakovskiy, “Methods of automated HRV-based diagnostics”, submitted (in Russian)
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[5] O.V. Senyukova and V.V. Gavrishchaka, “Ensemble Decomposition Learning for Optimal Utilization of Implicitly Encoded Knowledge in Biomedical Applications”, In: IASTED International Conference on Computational Intelligence and Bioinformatics. Pittsburgh, USA; 2011. p. 69-73
PRESENTATION SLIDES (PDF)
[4] O.V. Senyukova and V.V. Gavrishchaka, “Diagnostics of complex and rare abnormalities using ensemble decomposition learning”, In: International Conference on Computer and Computational Intelligence. Bangkok, Thailand; 2011, p. 19-26
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[1] V.V. Gavrishchaka, M.E. Koepke, and O.N. Ulyanova, “Ensemble learning frameworks for the discovery of multi-component quantitative models in biomedical applications”, in IEEE Proceedings of the 2-nd International Conference on Computer Modeling and Simulation (ICCMS-2010)
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