Radiomics-based interpretable machine learning model from multiphasic CT imaging for predicting pathological grade in upper tract urothelial carcinoma: a multicenter study.
Saved in:
| Title: | Radiomics-based interpretable machine learning model from multiphasic CT imaging for predicting pathological grade in upper tract urothelial carcinoma: a multicenter study. |
|---|---|
| Authors: | Yuan Z; Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China., Mei Y; Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China., Peng X; Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China., Wei Z; Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China., Xv Y; Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China., Xiao B; Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China., Xiao M; Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China. |
| Source: | Frontiers in oncology [Front Oncol] 2026 Jun 23; Vol. 16, pp. 1844559. Date of Electronic Publication: 2026 Jun 23 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101568867 Publication Model: eCollection Cited Medium: Print ISSN: 2234-943X (Print) Linking ISSN: 2234943X NLM ISO Abbreviation: Front Oncol Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
