ArticleInternational journal of endocrinology2024
Predictive Factors for the Efficacy of Radioactive Iodine Treatment of Graves' Disease: An Experience From 613 Chinese Patients.
Article in International journal of endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Multiple machine learning models for the prediction of an early response to radioactive iodine therapy in hyperthyroidism: ablative dose concept.Thyroid research · 2026Article
- Non-linear association between thyroid scintigraphy-derived thyroid weight and I-131 treatment efficacy in graves' disease: a multicenter restricted cubic spline and threshold analysis.Frontiers in endocrinology · 2026Article
- Predictive factors for the efficacy of radioiodine therapy in patients with Graves' disease.Nuclear medicine communications · 2025Article
- 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.Frontiers in endocrinology · 2025Article
- From data to decision: an interpretable machine learning model for optimizing RAI therapy in Graves' hyperthyroidism.Frontiers in endocrinology · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.