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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Detalles Bibliográficos
Autores principales: Tang, Fuk-Hay, Fong, Yee-Wai, Yung, Shing-Hei, Wong, Chi-Kan, Tu, Chak-Lap, Chan, Ming-To
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10452490/
https://www.ncbi.nlm.nih.gov/pubmed/37626590
http://dx.doi.org/10.3390/biomedicines11082093

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10452490/
https://www.ncbi.nlm.nih.gov/pubmed/37626590
http://dx.doi.org/10.3390/biomedicines11082093

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