An interpretable multimodal machine learning model for predicting malignancy of thyroid nodules in low-resource scenarios.

IF 3.3 3区医学 Q3 ENDOCRINOLOGY & METABOLISM

BMC Endocrine Disorders Pub Date : 2025-10-16 DOI:10.1186/s12902-025-02031-x

Fuqiang Ma, Fengchang Yu, Xinyu Gu, Lihua Zhang, Zhilin Lu, Lele Zhang, Herong Mao, Nan Xiang

引用次数: 0

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一个可解释的多模态机器学习模型，用于预测低资源情况下甲状腺结节的恶性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BMC Endocrine Disorders ENDOCRINOLOGY & METABOLISM-

CiteScore

4.40

自引率

0.00%

发文量

280

审稿时长

>12 weeks

期刊介绍： BMC Endocrine Disorders is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of endocrine disorders, as well as related molecular genetics, pathophysiology, and epidemiology.