Optimising Pharmacovigilance Efficiency with MLIT (Machine Learning for Intelligent Triage): A Tool for Statistical Safety Alerts
- DOI
- 10.1007/s40264-026-01696-0
- Published
- 2026-08-10
- Container
- Drug Safety
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1007/s40264-026-01696-0,
title = {Optimising Pharmacovigilance Efficiency with MLIT (Machine Learning for Intelligent Triage): A Tool for Statistical Safety Alerts},
author = {Luciano Ciccarelli and Olivia Mahaux and Christie Roshan and Ami Fofana and Anna Kawka and Emilia Occhipinti and Mariapia Possidente and Silvia Cenci and Jeffery L. Painter and Andrew Bate},
year = {2026},
journal = {Drug Safety},
doi = {10.1007/s40264-026-01696-0},
url = {https://doi.org/10.1007/s40264-026-01696-0}
}RIS
TY - JOUR TI - Optimising Pharmacovigilance Efficiency with MLIT (Machine Learning for Intelligent Triage): A Tool for Statistical Safety Alerts AU - Luciano Ciccarelli AU - Olivia Mahaux AU - Christie Roshan AU - Ami Fofana AU - Anna Kawka AU - Emilia Occhipinti AU - Mariapia Possidente AU - Silvia Cenci AU - Jeffery L. Painter AU - Andrew Bate PY - 2026 JO - Drug Safety DO - 10.1007/s40264-026-01696-0 UR - https://doi.org/10.1007/s40264-026-01696-0 ER -
APA
Ciccarelli, L., Mahaux, O., Roshan, C., Fofana, A., Kawka, A., Occhipinti, E., Possidente, M., Cenci, S., Painter, J. L., & Bate, A. (2026). Optimising Pharmacovigilance Efficiency with MLIT (Machine Learning for Intelligent Triage): A Tool for Statistical Safety Alerts. Drug Safety. https://doi.org/10.1007/s40264-026-01696-0
Source records
- crossref · retrieved 2026-09-27T03:15:42.939Z