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用机器学习预测图像引导疗法的治疗反应--肝细胞癌的跨动脉治疗实例

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Medicina

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JoVE Journal Medicina

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

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用机器学习预测图像引导疗法的治疗反应--肝细胞癌的跨动脉治疗实例

DOI:

10.3791/58382-v

•

04:09 min

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October 10, 2018

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Aaron Abajian, Nikitha Murali, Lynn Jeanette Savic², Fabian Max Laage-Gaupp, Nariman Nezami, James S. Duncan, Todd Schlachter, MingDe Lin, Jean-François Geschwind, Julius Chapiro

¹Department of Radiology and Biomedical Imaging,Yale School of Medicine, ²Department of Diagnostic and Interventional Radiology,Universitätsmedizin Charité Berlin, ³Department of Biomedical Engineering,Yale School of Engineering and Applied Science, ⁴Philips Research North America, ⁵Prescience Labs

Capítulos

00:04Título
00:59Structured Clinical Data Feature Extraction, Aggregation, and Reduction
03:01Results: Machine Learning Algorithm Performance
03:45Conclusion

Summary

Tadução automática

动脉内治疗是不能接受手术切除的肝癌患者的护理标准。提出了一种预测这些疗法反应的方法。该技术使用预先程序的临床、人口学和影像学信息来训练能够预测治疗前反应的机器学习模型。

Tags

Keywords: Machine Learning Image-guided Therapy Hepatocellular Carcinoma Trans-arterial Treatment Feature Extraction Binarization Model Training Outcome Prediction

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