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Peer-reviewedCC BYPharmaceuticals (Basel, Switzerland)

Multi-Label Classification of Adverse Drug Reactions Using a Hybrid Approach Integrating Support Vector Machine, Random Forest and Extreme Gradient Boosting

  • Ana-Maria Cucos1
  • Zsolt Gáll2
  • László Barna Iantovics3
  1. 1Doctoral School of Letters, Humanities and Applied Sciences, George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Targu Mures, 540142 Targu Mures, Romania;
  2. 2Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Targu Mures, 540142 Targu Mures, Romania
  3. 3Electrical Engineering and Information Technology Department, George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Targu Mures, 540142 Targu Mures, Romania;
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Cite

BibTeXRIS
BibTeX
@article{cucos2026multilabel,
  title = {{Multi-Label Classification of Adverse Drug Reactions Using a Hybrid Approach Integrating Support Vector Machine, Random Forest and Extreme Gradient Boosting}},
  author = {Ana-Maria Cucos and Zsolt Gáll and László Barna Iantovics},
  journal = {Pharmaceuticals (Basel, Switzerland)},
  year = {2026},
  month = oct,
  url = {https://europepmc.org/article/PMC/PMC13708647},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Multi-Label Classification of Adverse Drug Reactions Using a Hybrid Approach Integrating Support Vector Machine, Random Forest and Extreme Gradient Boosting
AU  - Ana-Maria Cucos
AU  - Zsolt Gáll
AU  - László Barna Iantovics
PY  - 2026
DA  - 2026/10/01
JO  - Pharmaceuticals (Basel, Switzerland)
UR  - https://europepmc.org/article/PMC/PMC13708647
SN  - 1424-8247
ER  -