Predicting Function Related Pain Outcomes using Comorbidity and Age Dependent Model

Aleksandar Jeremic, Dejan Nikolic, Dejan Nikolic, Milena Santric Milicevic, Milena Santric Milicevic, Milena Santric Milicevic

2020

Abstract

Effective pain management can significantly improve quality of life and outcomes for various types of patients (e.g. elderly, adult, young). In order to improve our understanding of patients’ response to pain we need to develop adequate signal processing techniques that would enable us to understand underlying interdependencies. To this purpose in this paper we develop several different algorithms that can predict function related pain outcomes using a large database obtained as a part of the national health survey. As a part of the survey the respondents provided detailed information about general health care state, acute and chronic problems as well as personal perception of pain associated with performing two simple talks: walking on the flat surface and walking upstairs. We model the correspondent responses using parametric and non-parametric models and use health indicators (both chronic and acute) as explanatory variables. For the binomial model we propose parametric age dependent model and then compare its performance to the performance of the multinomial and histogram models.

Paper Citation

in Harvard Style

Jeremic A., Nikolic D., Kostadinovic M. and Milicevic M. (2020). Predicting Function Related Pain Outcomes using Comorbidity and Age Dependent Model. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 4: BIOSIGNALS; ISBN 978-989-758-398-8, SciTePress, pages 319-323. DOI: 10.5220/0009167403190323

in Bibtex Style

@conference{biosignals20,
author={Aleksandar Jeremic and Dejan Nikolic and Milena Santric Kostadinovic and Milena Santric Milicevic},
title={Predicting Function Related Pain Outcomes using Comorbidity and Age Dependent Model},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 4: BIOSIGNALS},
year={2020},
pages={319-323},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009167403190323},
isbn={978-989-758-398-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 4: BIOSIGNALS
TI - Predicting Function Related Pain Outcomes using Comorbidity and Age Dependent Model
SN - 978-989-758-398-8
AU - Jeremic A.
AU - Nikolic D.
AU - Kostadinovic M.
AU - Milicevic M.
PY - 2020
SP - 319
EP - 323
DO - 10.5220/0009167403190323
PB - SciTePress