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Deep learning-based ultrasound assessment for predicting early recurrence risk after radiofrequency ablation in hepatocellular carcinoma
Specialists' Article | 更新时间:2026-03-25
    • Deep learning-based ultrasound assessment for predicting early recurrence risk after radiofrequency ablation in hepatocellular carcinoma

    • Experts from Harbin Medical University use deep learning technology to construct predictive models based on ultrasound and contrast-enhanced ultrasound images, accurately predicting early recurrence of liver cancer after radiofrequency ablation, providing a new tool for preoperative screening of high-risk patients and developing follow-up plans.
    • Oncoradiology   Vol. 35, Issue 1, Pages: 32-42(2026)
    • DOI:10.19732/j.cnki.2096-6210.2026.01.005    

      CLC: R735.7;R445.1
    • Received:27 November 2025

      Revised:2026-02-04

      Published:28 February 2026

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  • ZHANG Y, SUN W Q, CHEN YCitation:, et al. Deep learning-based ultrasound assessment for predicting early recurrence risk after radiofrequency ablation in hepatocellular carcinoma[J]. Oncoradiology, 2026, 35(1): 32-42. DOI: 10.19732/j.cnki.2096-6210.2026.01.005.

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Related Author

Kunpeng CAO
Chaoli XU
Xinyue WANG
Ya YUAN
Hua SHU
Xinhua YE
Lu LI
QIN Qiong

Related Institution

Department of Ultrasound, The First Affiliated Hospital with Nanjing Medical University
Department of Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University
Department of Medical Ultrasonics, Guangxi Hospital Division of The First Affiliated Hospital, Sun Yat-sen University
Department of Ultrasound, Zhongshan Hospital, Fudan University
Institute of Ultrasound in Medicine and Engineering, Fudan University
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