Integrative Machine Learning Approach for Predicting Resistance to First-generation Receptor Ligands in Acromegaly
The CatBoost-based calculator effectively predicts fgSRLs treatment response in acromegaly patients. Prospective validation is required before clinical implementation.
Authors
- Songchang Shi (ORCID: https://orcid.org/0000-0001-5793-569X)
- Edward R. Laws (ORCID: https://orcid.org/0000-0003-4804-9535)
- Wei Lin (ORCID: https://orcid.org/0000-0002-0455-8752)
- Zheng Yuanyuan (ORCID: https://orcid.org/0009-0006-6044-9442)
- Timothy R. Smith (ORCID: https://orcid.org/0009-0003-0691-7530)
- Le Min (ORCID: https://orcid.org/0000-0003-4363-1139)
Institutions
- Brigham and Women's Hospital (US)
- Fujian Medical University (CN)
- Harvard University (US)
- Fujian Provincial Hospital (CN)
Publication Details
- Journal
- The Journal of Clinical Endocrinology & Metabolism
- Published
- 2025-06-21
- DOI
- https://doi.org/10.1210/clinem/dgaf375
- Citations
- 2
- Primary Topic
- Pituitary Gland Disorders and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 2.59
Funders
- Pfizer