XGBPred-ACSM: A Hybrid Descriptor-Driven XGBoost Framework for Anticancer Small Molecule Prediction
: The study has brought into focus the transformational effect of machine learning in modern computational oncology and rational drug design pipelines.
Authors
- Thirumurthy Madhavan (ORCID: https://orcid.org/0000-0001-5625-1210)
- Anuradha Thiagarajan
- Honglae Sohn (ORCID: https://orcid.org/0000-0001-6399-1057)
- Priya Dharshini Balaji (ORCID: https://orcid.org/0000-0002-7213-6084)
- Subathra Selvam (ORCID: https://orcid.org/0009-0004-0850-7997)
Institutions
- SRM Institute of Science and Technology (IN)
- Chosun University (KR)
- Meenakshi Academy of Higher Education and Research (IN)
Publication Details
- Journal
- Pharmaceuticals
- Published
- 2026-04-17
- DOI
- https://doi.org/10.3390/ph19040635
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Chosun University