Interpretable machine learning for hikikomori screening: The adaptive HRI-15

Daiana Colledani, Pasquale Anselmi, Lucia Monacis, Bruno Genetti, Daniele Fassinato, Luis J. Gomez Perez, Adele Minutillo, Luisa Mastrobattista, Claudia Mortali

Open source

DOI: 10.1371/journal.pone.0355595
Published: 2026-08-20
Container: PLOS One
Publisher: Public Library of Science (PLoS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0355595,
  title = {Interpretable machine learning for hikikomori screening: The adaptive HRI-15},
  author = {Daiana Colledani and Pasquale Anselmi and Lucia Monacis and Bruno Genetti and Daniele Fassinato and Luis J. Gomez Perez and Adele Minutillo and Luisa Mastrobattista and Claudia Mortali},
  year = {2026},
  journal = {PLOS One},
  doi = {10.1371/journal.pone.0355595},
  url = {https://doi.org/10.1371/journal.pone.0355595}
}

RIS

TY  - JOUR
TI  - Interpretable machine learning for hikikomori screening: The adaptive HRI-15
AU  - Daiana Colledani
AU  - Pasquale Anselmi
AU  - Lucia Monacis
AU  - Bruno Genetti
AU  - Daniele Fassinato
AU  - Luis J. Gomez Perez
AU  - Adele Minutillo
AU  - Luisa Mastrobattista
AU  - Claudia Mortali
PY  - 2026
JO  - PLOS One
DO  - 10.1371/journal.pone.0355595
UR  - https://doi.org/10.1371/journal.pone.0355595
ER  -

APA

Colledani, D., Anselmi, P., Monacis, L., Genetti, B., Fassinato, D., Perez, L. J. G., Minutillo, A., Mastrobattista, L., & Mortali, C. (2026). Interpretable machine learning for hikikomori screening: The adaptive HRI-15. PLOS One. https://doi.org/10.1371/journal.pone.0355595

Source records

crossref · retrieved 2026-09-25T10:49:08.348Z