R-GCRED: a retrieval-grounded and calibrated risk estimation for depression prediction and screening recommendation framework

Firas Saidi, Marwa Almulla

Open source

DOI: 10.3389/frai.2026.1931579
Published: 2026-10-06
Container: Frontiers in Artificial Intelligence
Publisher: Frontiers Media SA
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3389/frai.2026.1931579,
  title = {R-GCRED: a retrieval-grounded and calibrated risk estimation for depression prediction and screening recommendation framework},
  author = {Firas Saidi and Marwa Almulla},
  year = {2026},
  journal = {Frontiers in Artificial Intelligence},
  doi = {10.3389/frai.2026.1931579},
  url = {https://doi.org/10.3389/frai.2026.1931579}
}

RIS

TY  - JOUR
TI  - R-GCRED: a retrieval-grounded and calibrated risk estimation for depression prediction and screening recommendation framework
AU  - Firas Saidi
AU  - Marwa Almulla
PY  - 2026
JO  - Frontiers in Artificial Intelligence
DO  - 10.3389/frai.2026.1931579
UR  - https://doi.org/10.3389/frai.2026.1931579
ER  -

APA

Saidi, F., & Almulla, M. (2026). R-GCRED: a retrieval-grounded and calibrated risk estimation for depression prediction and screening recommendation framework. Frontiers in Artificial Intelligence. https://doi.org/10.3389/frai.2026.1931579

Source records

crossref · retrieved 2026-11-09T20:14:17.259Z