دورية أكاديمية
A new method applied for explaining the landing patterns: Interpretability analysis of machine learning
| العنوان: | A new method applied for explaining the landing patterns: Interpretability analysis of machine learning |
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| المؤلفون: | Datao Xu, Huiyu Zhou, Wenjing Quan, Ukadike Chris Ugbolue, Fekete Gusztav, Yaodong Gu |
| المصدر: | Heliyon, Vol 10, Iss 4, Pp e26052- (2024) |
| بيانات النشر: | Elsevier, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Science (General) LCC:Social sciences (General) |
| مصطلحات موضوعية: | Landing pattern recognition, Clinical diagnosis, Biomechanics, Explainable machine learning, Layer-wise relevance propagation, Science (General), Q1-390, Social sciences (General), H1-99 |
| الوصف: | As one of many fundamental sports techniques, the landing maneuver is also frequently used in clinical injury screening and diagnosis. However, the landing patterns are different under different constraints, which will cause great difficulties for clinical experts in clinical diagnosis. Machine learning (ML) have been very successful in solving a variety of clinical diagnosis tasks, but they all have the disadvantage of being black boxes and rarely provide and explain useful information about the reasons for making a particular decision. The current work validates the feasibility of applying an explainable ML (XML) model constructed by Layer-wise Relevance Propagation (LRP) for landing pattern recognition in clinical biomechanics. This study collected 560 groups landing data. By incorporating these landing data into the XML model as input signals, the prediction results were interpreted based on the relevance score (RS) derived from LRP. The interpretation obtained from XML was evaluated comprehensively from the statistical perspective based on Statistical Parametric Mapping (SPM) and Effect Size. The RS has excellent statistical characteristics in the interpretation of landing patterns between classes, and also conforms to the clinical characteristics of landing pattern recognition. The current work highlights the applicability of XML methods that can not only satisfy the traditional decision problem between classes, but also largely solve the lack of transparency in landing pattern recognition. We provide a feasible framework for realizing interpretability of ML decision results in landing analysis, providing a methodological reference and solid foundation for future clinical diagnosis and biomechanical analysis. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2405-8440 |
| Relation: | http://www.sciencedirect.com/science/article/pii/S2405844024020838; https://doaj.org/toc/2405-8440 |
| DOI: | 10.1016/j.heliyon.2024.e26052 |
| URL الوصول: | https://doaj.org/article/fa5213574cf24967855545bf28ebb9a6 |
| رقم الأكسشن: | edsdoj.fa5213574cf24967855545bf28ebb9a6 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 24058440 |
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| DOI: | 10.1016/j.heliyon.2024.e26052 |