A machine learning radiomics based on enhanced computed tomography to predict neoadjuvant immunotherapy for resectable esophageal squamous cell carcinoma.
Saved in:
| Title: | A machine learning radiomics based on enhanced computed tomography to predict neoadjuvant immunotherapy for resectable esophageal squamous cell carcinoma. |
|---|---|
| Authors: | Wang JL; Department of Biotherapy, Cancer Center, West China Hospital of Sichuan University, Chengdu, China.; West China School of Medicine, Sichuan University, Chengdu, China., Tang LS; Department of Biotherapy, Cancer Center, West China Hospital of Sichuan University, Chengdu, China.; West China School of Medicine, Sichuan University, Chengdu, China., Zhong X; Department of Radiology, West China Hospital, Sichuan University, Chengdu, China., Wang Y; West China School of Medicine, Sichuan University, Chengdu, China., Feng YJ; West China School of Medicine, Sichuan University, Chengdu, China., Zhang Y; Department of Radiology, West China Hospital, Sichuan University, Chengdu, China., Liu JY; Department of Biotherapy, Cancer Center, West China Hospital of Sichuan University, Chengdu, China. |
| Source: | Frontiers in immunology [Front Immunol] 2024 Jun 14; Vol. 15, pp. 1405146. Date of Electronic Publication: 2024 Jun 14 (Print Publication: 2024). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101560960 Publication Model: eCollection Cited Medium: Internet ISSN: 1664-3224 (Electronic) Linking ISSN: 16643224 NLM ISO Abbreviation: Front Immunol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1664-3224 |
|---|---|
| DOI: | 10.3389/fimmu.2024.1405146 |
