New prognostic models for extranodal natural killer T-cell lymphoma, nasal-type using Cox regression and machine learning
Author:
Publisher
AME Publishing Company
Subject
Cancer Research,Radiology Nuclear Medicine and imaging,Oncology
Link
https://tcr.amegroups.com/article/download/49367/pdf
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Minimal residual disease detection in lymphoma: methods, procedures and clinical significance;Frontiers in Immunology;2024-08-12
2. A Nomogram Model Based on the Inflammation-Immunity-Nutrition Score (IINS) and Classic Clinical Indicators for Predicting Prognosis in Extranodal Natural Killer/T-Cell Lymphoma;Journal of Inflammation Research;2024-04
3. Application of machine learning in the management of lymphoma: Current practice and future prospects;DIGITAL HEALTH;2024-01
4. Integrative Prognostic Machine Learning Models in Mantle Cell Lymphoma;Cancer Research Communications;2023-08-02
5. The Novel Prognostic Index Model of Combining Circulating Tumor DNA and PINK-E Predicts the Clinical Outcomes for Newly Diagnosed Extranodal NK/T-cell Lymphoma;HemaSphere;2022-12-20
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