sj-xlsx-3-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 - Forschungsportal der Leuphana Universität Lüneburg

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Supplemental material, sj-xlsx-3-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

Datum zugänglich gemacht	16.05.2024
Verlag	SAGE Publications Inc.

Ansprechpartner

Burkhardt Funk

DOI
10.25384/sage.25836893

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https://sage.figshare.com/articles/dataset/sj-xlsx-3-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/25836893

1 Zeitschriftenaufsätze

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 S.
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › Begutachtung

Open Access
13 Zitate (Scopus)

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sj-xlsx-3-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

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Publikationen

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

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