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A deep learning fusion network trained with clinical and high-frequency ultrasound images in the multi-classification of skin diseases in comparison with dermatologists: a prospective and multicenter study.
Zhu AQ, Wang Q, Shi YL, Ren WW, Cao X, Ren TT, Wang J, Zhang YQ, Sun YK, Chen XW, Lai YX, Ni N, Chen YC, Hu JL, Mou LC, Zhao YJ, Liu YQ, Sun LP, Zhu XX, Xu HX, Guo LH; China Alliance of Multi-Center Clinical Study for Ultrasound (Ultra-Chance). Zhu AQ, et al. EClinicalMedicine. 2024 Jan 5;67:102391. doi: 10.1016/j.eclinm.2023.102391. eCollection 2024 Jan. EClinicalMedicine. 2024. PMID: 38274117 Free PMC article.
The monomodal convolutional neural network (CNN) model was trained and validated with the same close-up images for comparison. Subsequently, we did a prospective and multicenter study in China. Both CNN models were tested prospectively on 422 cases from 4 hospitals and com …
The monomodal convolutional neural network (CNN) model was trained and validated with the same close-up images for comparison. Subsequently, …
Three-dimensional convolutional neural network model to identify clinically significant prostate cancer in transrectal ultrasound videos: a prospective, multi-institutional, diagnostic study.
Sun YK, Zhou BY, Miao Y, Shi YL, Xu SH, Wu DM, Zhang L, Xu G, Wu TF, Wang LF, Yin HH, Ye X, Lu D, Han H, Xiang LH, Zhu XX, Zhao CK, Xu HX; China Alliance of Multi-Center Clinical Study for Ultrasound (Ultra-Chance). Sun YK, et al. EClinicalMedicine. 2023 Jun 9;60:102027. doi: 10.1016/j.eclinm.2023.102027. eCollection 2023 Jun. EClinicalMedicine. 2023. PMID: 37333662 Free PMC article.
More studies to determine how AI models better integrate into routine practice and randomized controlled trials to show the values of these models in real clinical applications are warranted. FUNDING: The National Natural Science Foundation of China (Grants 82202174 and 82 …
More studies to determine how AI models better integrate into routine practice and randomized controlled trials to show the values of these …
A multi-parameter intrahepatic cholangiocarcinoma scoring system based on modified contrast-enhanced ultrasound LI-RADS M criteria for differentiating intrahepatic cholangiocarcinoma from hepatocellular carcinoma.
Wang LF, Guan X, Shen YT, Zhou BY, Sun YK, Li XL, Yin HH, Lu D, Ye X, Hu XY, Yang DH, Xia HS, Wang X, Lu Q, Han H, Xu HX, Zhao CK; China Alliance of Multi-Center Clinical Study for Ultrasound (Ultra-Chance). Wang LF, et al. Abdom Radiol (NY). 2024 Feb;49(2):458-470. doi: 10.1007/s00261-023-04114-6. Epub 2024 Jan 16. Abdom Radiol (NY). 2024. PMID: 38225379