An Unsupervised Machine Learning Framework for Early Detection of Acute Psychological Distress in Isolated Populations

Femi Temitope Johnson, Oladapo Elugbadebo, Sunday Akinyele, Ogunrinde Bosede, Olukumoro Olukumoro

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DOI: 10.66224/ist.202603.11.03
Published: 1
Container: InfoScience Trends
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.66224/ist.202603.11.03,
  title = {An Unsupervised Machine Learning Framework for Early Detection of Acute Psychological Distress in Isolated Populations},
  author = {Femi Temitope Johnson and Oladapo Elugbadebo and Sunday Akinyele and Ogunrinde Bosede and Olukumoro Olukumoro},
  year = {2026},
  journal = {InfoScience Trends},
  doi = {10.66224/ist.202603.11.03},
  url = {https://doi.org/10.66224/ist.202603.11.03}
}

RIS

TY  - JOUR
TI  - An Unsupervised Machine Learning Framework for Early Detection of Acute Psychological Distress in Isolated Populations
AU  - Femi Temitope Johnson
AU  - Oladapo Elugbadebo
AU  - Sunday Akinyele
AU  - Ogunrinde Bosede
AU  - Olukumoro Olukumoro
PY  - 2026
JO  - InfoScience Trends
DO  - 10.66224/ist.202603.11.03
UR  - https://doi.org/10.66224/ist.202603.11.03
ER  -

APA

Johnson, F. T., Elugbadebo, O., Akinyele, S., Bosede, O., & Olukumoro, O. (2026). An Unsupervised Machine Learning Framework for Early Detection of Acute Psychological Distress in Isolated Populations. InfoScience Trends. https://doi.org/10.66224/ist.202603.11.03

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doaj · retrieved 2026-09-25T10:55:32.258Z