ItemComplex: A Python-based visualization framework for ex-post organization and integration of large language-based datasets

Abstract Background Nowadays, both researchers and clinicians alike have to deal with increasingly larger datasets, specifically also in the context of mental health data. Sophisticated tools for dataset visualization of information from various item-based instruments, such as questionnaire data or...

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Detalles Bibliográficos

Principais autores:	Karina Janson, Karl Gottfried, Olaf Reis, Johannes Kornhuber, Anna Eichler, Michael Deuschle, Tobias Banaschewski, Frauke Nees, IMAC-Mind Consortium
Formato:	Artigo
Idioma:	Inglês
Publicado:	Cambridge University Press 2025-01-01
Series:	European Psychiatry
Assuntos:	big data constructs content networks data navigation data structuring data visualization items
Acceso en liña:	https://www.cambridge.org/core/product/identifier/S0924933825024575/type/journal_article
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