Machine Learning Model Based on Optimized Radiomics Feature from (18)F-FDG-PET/CT and Clinical Characteristics Predicts Prognosis of Multiple Myeloma: A Preliminary Study

Objects: To evaluate the prognostic value of radiomics features extracted from (18)F-FDG-PET/CT images and integrated with clinical characteristics and conventional PET/CT metrics in newly diagnosed multiple myeloma (NDMM) patients. Methods: We retrospectively reviewed baseline clinical information...

Descripción completa

Detalles Bibliográficos
Autores principales: Ni, Beiwen, Huang, Gan, Huang, Honghui, Wang, Ting, Han, Xiaofeng, Shen, Lijing, Chen, Yumei, Hou, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10059677/
https://www.ncbi.nlm.nih.gov/pubmed/36983281
http://dx.doi.org/10.3390/jcm12062280

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10059677/
https://www.ncbi.nlm.nih.gov/pubmed/36983281
http://dx.doi.org/10.3390/jcm12062280

Ejemplares similares