Causality-based tests to detect the influence of confounders on mobile health diagnostic applications: a comparison with restricted permutations

Machine learning practice is often impacted by confounders. Confounding can be particularly severe in remote digital health studies where the participants self-select to enter the study. While many different confounding adjustment approaches have been proposed in the literature, most of these method...

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Veröffentlicht in:	arXiv.org 2019-11
Hauptverfasser:	Neto, Elias Chaibub, Tummalacherla, Meghasyam, Mangravite, Lara, Larsson Omberg
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Causality Diagnostic software Diagnostic systems Machine learning Parkinson's disease Performance prediction Permutations
Online-Zugang:	Volltext
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