WindowSHAP: An efficient framework for explaining time-series classifiers based on Shapley values

[Display omitted] Unpacking and comprehending how black-box machine learning algorithms (such as deep learning models) make decisions has been a persistent challenge for researchers and end-users. Explaining time-series predictive models is useful for clinical applications with high stakes to unders...

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Veröffentlicht in:	Journal of biomedical informatics 2023-08, Vol.144, p.104438-104438, Article 104438
Hauptverfasser:	Nayebi, Amin, Tipirneni, Sindhu, Reddy, Chandan K., Foreman, Brandon, Subbian, Vignesh
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Benchmarking Brain Injuries, Traumatic - diagnosis Explainable artificial intelligence Humans Machine Learning Model interpretation Shapley value Time Factors Time-series data
Online-Zugang:	Volltext
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