Data-driven approach for modeling of control action impact on anemia dynamics based on energy-informational health state criteria

Olga Gerget, Dmitry Devyatykh, Maxim Shcherbakov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this work, spatial and time parameters were used to estimate the state of a biosystem on the strength of all attributes from integral criteria based on the Kullback information metric that is considered as a metric of a preferential behavior of a bio-object. Proximity of observed and preferential (reference) states is analyzed in the attribute space, where the proximity is normalized in the Mahalanobis model by an intraset distance of the reference state. Proposed approach can be considered as decision support instrument for medical experts evaluating possible outcomes of several treatment procedures. By modeling dynamics of individual integral criteria, the authors demonstrated the possibility of predicting the impact of sorbifer durules and mecsidol on the health state of pregnant women diagnosed with anemia. Experimental data included 8 blood properties from 92 pregnant women at different gestation periods measured at 3 timesteps: before; while; after applying treatment defined by medical experts. Treatment was considered as control action on biosystem and implicitly embedded into basic machine learning models such as linear regression and multilayer perceptrone. “Brute” approach to cross-validation identified several unique cases that could not be learned by models, due to lack of representativeness in original dataset and not model’s relative simplicity. Revealed anomalies were proven to be correct by medical experts from Tomsk neonatal health center.

Original languageEnglish
Title of host publicationCreativity in Intelligent Technologies and Data Science - 2nd Conference, CIT and DS 2017, Proceedings
EditorsPeter Groumpos, Alla Kravets, Maxim Shcherbakov, Marina Kultsova
PublisherSpringer Verlag
Pages833-846
Number of pages14
ISBN (Print)9783319655505
DOIs
Publication statusPublished - 2017
Event2nd Conference on Creativity in Intelligent Technologies and Data Science, CIT and DS 2017 - Volgograd, Russian Federation
Duration: 12 Sep 201714 Sep 2017

Publication series

NameCommunications in Computer and Information Science
Volume754
ISSN (Print)1865-0929

Conference

Conference2nd Conference on Creativity in Intelligent Technologies and Data Science, CIT and DS 2017
CountryRussian Federation
CityVolgograd
Period12.9.1714.9.17

Keywords

  • Anemia
  • Decision support system
  • Identification
  • Integral criteria
  • Kullback metrics
  • Prediction

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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