Predicting Recurrence for Patients with Head-Neck Squamous Cell Carcinoma Using Quantitative Ultrasound Based Radiomic Signatures Integrated with Machine Learning

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作者： Fatima, K. ^[1] ; Sannachi, L. ; Quiaiot, K. ; Suraweera, H. ; Saifuddin, M. ; Dasgupta, A. ; Cardenas, D. ; Leong, K. ; DiCenzo, D. ; Karam, I. ; Poon, I. ; Rahman, S. E. T. H. ; Jang, D. ; Gangeh, M. ; Garcia, E. ; Tabbarah, S. ; Sadeghi-Naini, A. ; Tran, W. ; Czarnota, G. J.

作者单位： Sunnybrook Hlth Sci Ctr, Toronto, ON, Canada ^[1]

发布时间 2020-08-21

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International Journal of Radiation Oncology, Biology, Physics

2019年105卷1S期

E436-E437页

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Predicting Recurrence for Patients with Head-Neck Squamous Cell Carcinoma Using Quantitative Ultrasound Based Radiomic Signatures Integrated with Machine Learning

International Journal of Radiation Oncology, Biology, Physics

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International Journal of Radiation Oncology, Biology, Physics

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Predicting Recurrence for Patients with Head-Neck Squamous Cell Carcinoma Using Quantitative Ultrasound Based Radiomic Signatures Integrated with Machine Learning

International Journal of Radiation Oncology, Biology, Physics

相似文献

International Journal of Radiation Oncology, Biology, Physics

相关期刊

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