An Intelligent Clinical Decision Support System for Analyzing Neuromusculoskeletal Disorders

Nigar Şen Köktaş, Neşe Yalabik, Güneş Yavuzer

Abstract

This study presents a clinical decision support system for detecting and further analyzing neuromusculoskeletal disorders using both clinical and gait data. The system is composed of a database storing disease characteristics, symptoms and gait data of the subjects, a combined pattern classifier that processes the data and user friendly interfaces. Data is mainly obtained through Computerized Gait Analysis, which can be defined as numerical representation of the mechanical measurements of human walking patterns. The decision support system uses mainly a combined classifier to incorporate the different types of data for better accuracy. A decision tree is developed with Multilayer Perceptrons at the leaves. The system is planned to be used for various neuromusculoskeletal disorders such as Cerebral Palsy (CP), stroke, and Osteoarthritis (OA). First experiments are performed with OA. Subjects are classified into four OA-severity categories, formed in accordance with the Kellgren-Lawrence scale: “Normal”, “Mild”, “Moderate”, and “Severe”. A classification accuracy of 80% is achieved on the test set. To complete the system, a patient follow-up mechanism is also designed.

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Paper Citation


in Harvard Style

Şen Köktaş N., Yalabik N. and Yavuzer G. (2008). An Intelligent Clinical Decision Support System for Analyzing Neuromusculoskeletal Disorders . In Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2008) ISBN 978-989-8111-42-5, pages 29-37. DOI: 10.5220/0001732700290037


in Bibtex Style

@conference{pris08,
author={Nigar Şen Köktaş and Neşe Yalabik and Güneş Yavuzer},
title={An Intelligent Clinical Decision Support System for Analyzing Neuromusculoskeletal Disorders},
booktitle={Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2008)},
year={2008},
pages={29-37},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001732700290037},
isbn={978-989-8111-42-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2008)
TI - An Intelligent Clinical Decision Support System for Analyzing Neuromusculoskeletal Disorders
SN - 978-989-8111-42-5
AU - Şen Köktaş N.
AU - Yalabik N.
AU - Yavuzer G.
PY - 2008
SP - 29
EP - 37
DO - 10.5220/0001732700290037