利用光谱计算机断层扫描和机器学习对慢性乙型肝炎病毒患者进行术前预测的文章综述。

IF 4.3 3区医学 Q1 GASTROENTEROLOGY & HEPATOLOGY

World Journal of Gastroenterology Pub Date : 2024-10-14 DOI:10.3748/wjg.v30.i38.4239

Yao-Qian Yuan, Qian-Qian Chen

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引用次数: 0

摘要

这封信评论了一篇文章，该文章开发并测试了一种机器学习模型，通过结合临床指征和频谱计算机断层扫描特征，准确预测淋巴管侵犯/神经周围侵犯状态。我们回顾了该研究的研究内容、方法、结论、优缺点，并介绍了这项工作的后续研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Review on article of preoperative prediction in chronic hepatitis B virus patients using spectral computed tomography and machine learning.

This letter comments on the article that developed and tested a machine learning model that predicts lymphovascular invasion/perineural invasion status by combining clinical indications and spectral computed tomography characteristics accurately. We review the research content, methodology, conclusions, strengths and weaknesses of the study, and introduce follow-up research to this work.

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来源期刊

World Journal of Gastroenterology 医学-胃肠肝病学

CiteScore

7.80

自引率

4.70%

发文量

464

审稿时长

2.4 months

期刊介绍： The primary aims of the WJG are to improve diagnostic, therapeutic and preventive modalities and the skills of clinicians and to guide clinical practice in gastroenterology and hepatology.