Radiomics-Clinical AI Model with Probability Weighted Strategy for Prognosis Prediction in Non-Small Cell Lung Cancer

Radiomics-Clinical AI Model with Probability Weighted Strategy for Prognosis Prediction in Non-Small Cell Lung Cancer

In this study, we propose a radiomics clinical probability-weighted model for the prediction of prognosis for non-small cell lung cancer (NSCLC). The model combines radiomics features extracted from radiotherapy (RT) planning images with clinical factors such as age, gender, histology, and tumor sta...

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Bibliographic Details
Main Authors: Fuk-Hay Tang, Yee-Wai Fong, Shing-Hei Yung, Chi-Kan Wong, Chak-Lap Tu, Ming-To Chan
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Biomedicines
Subjects:
radiomics
radiotherapy
artificial intelligence (AI)
prognosis prediction
clinical factors
machine learning
Online Access:https://www.mdpi.com/2227-9059/11/8/2093

Internet

https://www.mdpi.com/2227-9059/11/8/2093

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