Prediction of total iodine dose of I-131 therapy for Graves’ hyperthyroidism achieved remission status: a random forest regressor model approach to assess treatment efficacy
In conclusion, this study successfully developed and validated an RFR model that accurately predicts the TID for GH patients achieved remission. By integrating multi-dimensional features and providing interpretability through SHAP values, this model offers a sophisticated approach to dose personalization. This advancement has the potential to significantly improve <sup>131</sup>I treatment efficacy, minimize adverse effects such as hypothyroidism, and foster more precise, individualized patient care in GH.
Authors
- Kehua Liao
- Dan Meng (ORCID: https://orcid.org/0000-0001-8588-0235)
- Fahuan Song (ORCID: https://orcid.org/0000-0002-4110-5912)
- Yan Chen (ORCID: https://orcid.org/0000-0002-5317-1909)
- Lu Lu (ORCID: https://orcid.org/0000-0002-0960-1529)
- Shaozhou Mo
- Zeyong Sun
- Yuehua Li
- Xiaojuan Wei
- Wentan Huang
Institutions
- The People's Hospital of Guangxi Zhuang Autonomous Region (CN)
Publication Details
- Journal
- Frontiers in Endocrinology
- Published
- 2026-01-02
- DOI
- https://doi.org/10.3389/fendo.2025.1729926
- Primary Topic
- Thyroid Disorders and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00