Published on in Vol 9 (2023)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/45455, first published
.
Epidemiology and a Predictive Model of Prognosis Index Based on Machine Learning in Primary Breast Lymphoma: Population-Based Study
Epidemiology and a Predictive Model of Prognosis Index Based on Machine Learning in Primary Breast Lymphoma: Population-Based Study
Journals
- Xie S, Zhang W, Wu Y, Tang Z, Yang L, Xue Y, Lin J, Kang M. Application of predictive model based on CT radiomics and machine learning in diagnosis for occult locally advanced esophageal squamous cell carcinoma before treatment: A two-center study. Translational Oncology 2024;47:102050 View
- Zhao A, Sun X, Cheng W, Yang Y, Xiang B, Niu T. Epidemiology characteristics and clinical outcomes of composite Hodgkin lymphoma and diffuse large B-cell lymphoma using machine learning. The Oncologist 2025;30(4) View
- Cui Z, Liang Z, Liu C, Chen Y, Wang N, Liu B, Guo L, Song B. Prognostic assessment and intelligent prediction system for breast reduction surgery using improved swarm intelligence optimization. Frontiers in Medicine 2025;12 View
- Hou W, Li C, Wang Z, Wang W, Wan S, Zou B. Predicting Lymph Node Metastasis in Rectal Cancer: Development and Validation of a Machine Learning Model Using Clinical Data. JMIR Medical Informatics 2025;13:e73765 View