Predicting chronic pain in postoperative breast cancer patients with multiple machine learning and deep learning models - 12/10/21
Doi : 10.1016/j.jclinane.2021.110423
Ying Wang, MD a, 1, Yu Zhu, MS a, b, 1, Qiong Xue, MS a, 1, Muhuo Ji, MD a, Jianhua Tong, MS a, Jian-Jun Yang, MD a, ⁎ 
, Cheng-Mao Zhou, MD a, ⁎
, Cheng-Mao Zhou, MD a, ⁎ a Department of Anesthesiology, Pain and Perioperative Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China
b Anesthesia and Big Data Research Group, Department of Scientific Research, Zhaoqing Medical College, China
⁎Corresponding authors.
Highlights |
• | This is the first study to use a variety of machine learning and deep learning techniques to construct a predictive model for chronic post-surgical pain in patients with breast cancer. |
• | And the average machine learning algorithm model showed that age, endocrine therapy, radiotherapy and chemotherapy were the clinical risk factors for chronic pain after breast surgery. |
Keywords : Chronic postsurgical pain, Machine learning, Deep learning;XGB algorithm, CNNRNN
Plan
© 2021
Publié par Elsevier Masson SAS.
Vol 74
Article 110423- novembre 2021 Retour au numéro
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