SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media.
- DOI
- 10.1016/j.artmed.2017.10.003
- Published
- 2018 Jan
- Container
- Artificial intelligence in medicine
- Publisher
- Not recorded
- Open access
- unknown
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- 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.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1016/j.artmed.2017.10.003,
title = {SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media.},
author = {Liu J and Zhao S and Wang G},
year = {2018},
journal = {Artificial intelligence in medicine},
doi = {10.1016/j.artmed.2017.10.003},
url = {https://doi.org/10.1016/j.artmed.2017.10.003}
}RIS
TY - JOUR TI - SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media. AU - Liu J AU - Zhao S AU - Wang G PY - 2018 JO - Artificial intelligence in medicine DO - 10.1016/j.artmed.2017.10.003 UR - https://doi.org/10.1016/j.artmed.2017.10.003 ER -
APA
J, L., S, Z., & G, W. (2018). SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media.. Artificial intelligence in medicine. https://doi.org/10.1016/j.artmed.2017.10.003
Source records
- pubmed · retrieved 2026-09-26T21:03:40.784Z