Universität zu Köln

Duran, Ibrahim ORCID: 0000-0003-4044-8822, Stark, Christina, Saglam, Ahmet, Semmelweis, Alexandra, Wunram, Heidrun Lioba, Spiess, Karoline and Schoenau, Eckhard (2022). Artificial intelligence to improve efficiency of administration of gross motor function assessment in children with cerebral palsy. Dev. Med. Child Neurol., 64 (2). S. 228 - 235. HOBOKEN: WILEY. ISSN 1469-8749

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Abstract

Aim To create a reduced version of the 66-item Gross Motor Function Measure (rGMFM-66) using innovative artificial intelligence methods to improve efficiency of administration of the GMFM-66. Method This study was undertaken using information from an existing data set of children with cerebral palsy participating in a rehabilitation programme. Different self-learning approaches (random forest, support vector machine [SVM], and artificial neural network) were evaluated to estimate the GMFM-66 score with the fewest possible test items. Test agreements were evaluated (among other statistics) by intraclass correlation coefficients (ICCs). Results Overall, 1217 GMFM-66 assessments (509 females, mean age 8y 10mo [SD 3y 9mo]) at a single time and 187 GMFM-66 assessments and reassessments (80 females, mean age 8y 5mo [SD 3y 10mo]) after 1 year were evaluated. The model with SVM predicted the GMFM-66 scores most accurately. The ICCs of the rGMFM-66 and the full GMFM-66 were 0.997 (95% confidence interval [CI] 0.996-0.997) at a single time and 0.993 (95% CI 0.993-0.995) for the evaluation of the change over time. Interpretation The study shows that the efficiency of the full GMFM-66 assessment can be increased by using machine learning (self-learning algorithms). The presented rGMFM-66 score showed an excellent agreement with the full GMFM-66 score when applied to a single assessment and when evaluating the change over time.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Duran, Ibrahim UNSPECIFIED orcid.org/0000-0003-4044-8822 UNSPECIFIED Stark, Christina UNSPECIFIED UNSPECIFIED UNSPECIFIED Saglam, Ahmet UNSPECIFIED UNSPECIFIED UNSPECIFIED Semmelweis, Alexandra UNSPECIFIED UNSPECIFIED UNSPECIFIED Wunram, Heidrun Lioba UNSPECIFIED UNSPECIFIED UNSPECIFIED Spiess, Karoline UNSPECIFIED UNSPECIFIED UNSPECIFIED Schoenau, Eckhard UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-571585
DOI:	10.1111/dmcn.15010
Journal or Publication Title:	Dev. Med. Child Neurol.
Volume:	64
Number:	2
Page Range:	S. 228 - 235
Date:	2022
Publisher:	WILEY
Place of Publication:	HOBOKEN
ISSN:	1469-8749
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language RELIABILITY Multiple languages Clinical Neurology; Pediatrics Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/57158