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Updated: May 22, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

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诊断为赫特尔细胞癌的患者的术后预后:一种机器学习方法

Arnavaz Hajizadeh Barfejani1, Mohammad Reza Balali2, Nabgouri Younes3

  • 1Royal College of Surgeons in Ireland, Dublin, Ireland.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
|March 15, 2025
PubMed
概括

机器学习准确地预测了Hurthle细胞癌存活率. 根据这项研究,老年和晚期瘤阶段 (T分类) 恶化了结果,而女性性别改善了生存率.

关键词:
赫特尔细胞癌的癌症机器学习 机器学习幸存的生存方式甲状腺癌是什么?甲状腺癌是什么?

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Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
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