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An interpretable machine learning model based on contrast-enhanced CT parameters for predicting treatment response to conventional transarterial chemoembolization in patients with hepatocellular carcinoma.
Zhang L, Jin Z, Li C, He Z, Zhang B, Chen Q, You J, Ma X, Shen H, Wang F, Wu L, Ma C, Zhang S. Zhang L, et al. Among authors: zhang b, zhang s. Radiol Med. 2024 Mar;129(3):353-367. doi: 10.1007/s11547-024-01785-z. Epub 2024 Feb 14. Radiol Med. 2024. PMID: 38353864
Automated and reusable deep learning (AutoRDL) framework for predicting response to neoadjuvant chemotherapy and axillary lymph node metastasis in breast cancer using ultrasound images: a retrospective, multicentre study.
You J, Huang Y, Ouyang L, Zhang X, Chen P, Wu X, Jin Z, Shen H, Zhang L, Chen Q, Pei S, Zhang B, Zhang S. You J, et al. Among authors: zhang l, zhang b, zhang s, zhang x. EClinicalMedicine. 2024 Feb 27;69:102499. doi: 10.1016/j.eclinm.2024.102499. eCollection 2024 Mar. EClinicalMedicine. 2024. PMID: 38440400 Free PMC article.
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