Energy spectrum CT index‐based machine learning model predicts the effect of intravenous thrombolysis in lower limbs

To develop a noninvasive machine learning (ML) model based on energy spectrum computed tomography venography (CTV) indices for preoperatively predicting the effect of intravenous thrombolytic treatment in lower limbs. A total of 3492 slices containing thrombus regions from 58 veins in lower limbs in...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Rong, Yang, Junlin, Yin, Hongkun, Wu, Qian, Yu, Pengxin, Zhang, Wei, Li, Chenglong, Fan, Guohua, Ju, Shenghong, Cai, Wu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Medical Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10338802/
https://www.ncbi.nlm.nih.gov/pubmed/37254659
http://dx.doi.org/10.1002/acm2.14048

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10338802/
https://www.ncbi.nlm.nih.gov/pubmed/37254659
http://dx.doi.org/10.1002/acm2.14048

Ejemplares similares