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Cited by in F6Publishing
For: Ahmad Z, Rahim S, Zubair M, Abdul-Ghafar J. Artificial intelligence (AI) in medicine, current applications and future role with special emphasis on its potential and promise in pathology: present and future impact, obstacles including costs and acceptance among pathologists, practical and philosophical considerations. A comprehensive review. Diagn Pathol 2021;16:24. [PMID: 33731170 DOI: 10.1186/s13000-021-01085-4] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
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1 Nakajima K, Igata M, Higuchi R. Potential Role of Artificial Intelligence for the Previous Study Using Traditional Analysis. J Clin Med Res 2021;13:409-11. [PMID: 34394784 DOI: 10.14740/jocmr4568] [Reference Citation Analysis]
2 Ruini C, Schlingmann S, Jonke Ž, Avci P, Padrón-Laso V, Neumeier F, Koveshazi I, Ikeliani IU, Patzer K, Kunrad E, Kendziora B, Sattler E, French LE, Hartmann D. Machine Learning Based Prediction of Squamous Cell Carcinoma in Ex Vivo Confocal Laser Scanning Microscopy. Cancers (Basel) 2021;13:5522. [PMID: 34771684 DOI: 10.3390/cancers13215522] [Reference Citation Analysis]
3 Yan S, Zhang H, Wang J. Trends and hot topics in radiology, nuclear medicine and medical imaging from 2011-2021: a bibliometric analysis of highly cited papers. Jpn J Radiol 2022. [PMID: 35344133 DOI: 10.1007/s11604-022-01268-z] [Reference Citation Analysis]
4 Shi Z, Zhu C, Zhang Y, Wang Y, Hou W, Li X, Lu J, Guo X, Xu F, Jiang X, Wang Y, Liu J, Jin M. Deep learning for automatic diagnosis of gastric dysplasia using whole-slide histopathology images in endoscopic specimens. Gastric Cancer 2022. [PMID: 35394573 DOI: 10.1007/s10120-022-01294-w] [Reference Citation Analysis]
5 Flach RN, Fransen NL, Sonnen AFP, Nguyen TQ, Breimer GE, Veta M, Stathonikos N, van Dooijeweert C, van Diest PJ. Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective. Diagnostics 2022;12:1042. [DOI: 10.3390/diagnostics12051042] [Reference Citation Analysis]