Meta-Modeling with Drug Discovery Stack Regressor for Drug Discovery: An Explainable AI Perspective
This study highlights that explainable ensemble models can improve the reliability, interpretability, and applicability of AI in drug discovery. The framework is scalable for broader datasets and offers actionable insights for rational therapeutic development and regulatory alignment.
Authors
- A Sasithradevi (ORCID: https://orcid.org/0000-0001-5198-6648)
- M. Vijayalakshmi (ORCID: https://orcid.org/0000-0002-3751-7041)
- Spoorthi J.S. (ORCID: https://orcid.org/0009-0007-9308-2373)
Institutions
- Pioneer (Japan) (JP)
- Vellore Institute of Technology University (IN)
Publication Details
- Journal
- Current Drug Discovery Technologies
- Published
- 2025-10-27
- DOI
- https://doi.org/10.2174/0115701638405489251006073137
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00