A dual-stream deep learning architecture for business impact scoring and alert escalation

Mohammed Saad Javeed, Mst. Moushumi Khatun, Jobayar Alom, Rahomotul Islam, Hashibul Ahsan Shoaib

Open source

DOI: 10.1371/journal.pone.0350676
Published: 2026-07-13
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.0350676,
  title = {A dual-stream deep learning architecture for business impact scoring and alert escalation},
  author = {Mohammed Saad Javeed and Mst. Moushumi Khatun and Jobayar Alom and Rahomotul Islam and Hashibul Ahsan Shoaib},
  year = {2026},
  journal = {PLOS One},
  doi = {10.1371/journal.pone.0350676},
  url = {https://doi.org/10.1371/journal.pone.0350676}
}

RIS

TY  - JOUR
TI  - A dual-stream deep learning architecture for business impact scoring and alert escalation
AU  - Mohammed Saad Javeed
AU  - Mst. Moushumi Khatun
AU  - Jobayar Alom
AU  - Rahomotul Islam
AU  - Hashibul Ahsan Shoaib
PY  - 2026
JO  - PLOS One
DO  - 10.1371/journal.pone.0350676
UR  - https://doi.org/10.1371/journal.pone.0350676
ER  -

APA

Javeed, M. S., Khatun, M. M., Alom, J., Islam, R., & Shoaib, H. A. (2026). A dual-stream deep learning architecture for business impact scoring and alert escalation. PLOS One. https://doi.org/10.1371/journal.pone.0350676

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crossref · retrieved 2026-09-25T04:59:00.761Z