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For: Cheng CT, Wang Y, Chen HW, Hsiao PM, Yeh CN, Hsieh CH, Miao S, Xiao J, Liao CH, Lu L. A scalable physician-level deep learning algorithm detects universal trauma on pelvic radiographs. Nat Commun 2021;12:1066. [PMID: 33594071 DOI: 10.1038/s41467-021-21311-3] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Hsieh CI, Zheng K, Lin C, Mei L, Lu L, Li W, Chen FP, Wang Y, Zhou X, Wang F, Xie G, Xiao J, Miao S, Kuo CF. Automated bone mineral density prediction and fracture risk assessment using plain radiographs via deep learning. Nat Commun 2021;12:5472. [PMID: 34531406 DOI: 10.1038/s41467-021-25779-x] [Reference Citation Analysis]
2 Ye X, Guo D, Tseng C, Ge J, Hung T, Pai P, Ren Y, Zheng L, Zhu X, Peng L, Chen Y, Chen X, Chou C, Chen D, Yu J, Chen Y, Jiao F, Xin Y, Huang L, Xie G, Xiao J, Lu L, Yan S, Jin D, Ho T. Multi-Institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume Using Planning CT and FDG-PET/CT. Front Oncol 2022;11:785788. [DOI: 10.3389/fonc.2021.785788] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Liu FY, Chen CC, Cheng CT, Wu CT, Hsu CP, Fu CY, Chen SC, Liao CH, Lee MS. Automatic Hip Detection in Anteroposterior Pelvic Radiographs-A Labelless Practical Framework. J Pers Med 2021;11:522. [PMID: 34200151 DOI: 10.3390/jpm11060522] [Reference Citation Analysis]
4 Kuo RYL, Harrison C, Curran TA, Jones B, Freethy A, Cussons D, Stewart M, Collins GS, Furniss D. Artificial Intelligence in Fracture Detection: A Systematic Review and Meta-Analysis. Radiology 2022;:211785. [PMID: 35348381 DOI: 10.1148/radiol.211785] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
5 Sato Y, Takegami Y, Asamoto T, Ono Y, Hidetoshi T, Goto R, Kitamura A, Honda S. Artificial intelligence improves the accuracy of residents in the diagnosis of hip fractures: a multicenter study. BMC Musculoskelet Disord 2021;22:407. [PMID: 33941145 DOI: 10.1186/s12891-021-04260-2] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
6 Guermazi A, Tannoury C, Kompel AJ, Murakami AM, Ducarouge A, Gillibert A, Li X, Tournier A, Lahoud Y, Jarraya M, Lacave E, Rahimi H, Pourchot A, Parisien RL, Merritt AC, Comeau D, Regnard NE, Hayashi D. Improving Radiographic Fracture Recognition Performance and Efficiency Using Artificial Intelligence. Radiology 2021;:210937. [PMID: 34931859 DOI: 10.1148/radiol.210937] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 7.0] [Reference Citation Analysis]