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Updated: Jun 7, 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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使用XGBoost估计头发密度

Yi-Fan Wang1, Mei-Hua Hsu2, Max Yue-Feng Wang3

  • 1Institute of Information and Decision Sciences, National Taipei University of Business, Taipei, Taiwan.

International journal of cosmetic science
|November 17, 2024
PubMed
概括

这项研究引入了一种有效的XGBoost模型,用于自动估计头发密度,达到95.3%的准确性. 这种方法提高了临床头发分析的客观性,优于以前的方法.

关键词:
计算机辅助检测和诊断.头发的密度 头发的密度机器学习是机器学习.模式识别和分类模式的识别和分类皮肤 皮肤 皮肤

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