sj-xlsx-4-dhj-10.1177_20552076241248920 - Supplemental material for Dataset size versus homogeneity: A machine learning study on pooling intervention data in e-mental health dropout predictions - Research portal of the Leuphana University Lüneburg

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Supplemental material, sj-xlsx-4-dhj-10.1177_20552076241248920 for Dataset size versus homogeneity: A machine learning study on pooling intervention data in e-mental health dropout predictions by Kirsten Zantvoort, Nils Hentati Isacsson, Burkhardt Funk and Viktor Kaldo in DIGITAL HEALTH

Date made available	2024
Publisher	SAGE Publications Inc.

DOI
10.1177/20552076241248920

1 Journal articles

Dataset size versus homogeneity: A machine learning study on pooling intervention data in e-mental health dropout predictions
Zantvoort, K., Hentati Isacsson, N., Funk, B. & Kaldo, V., 2024, In: Digital Health. 10, 11 p.
Research output: Journal contributions › Journal articles › Research › peer-review

Open Access
13 Citations (Scopus)

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sj-xlsx-4-dhj-10.1177_20552076241248920 - Supplemental material for Dataset size versus homogeneity: A machine learning study on pooling intervention data in e-mental health dropout predictions

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DOI

Research output

Dataset size versus homogeneity: A machine learning study on pooling intervention data in e-mental health dropout predictions

Cite this