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Cited by in F6Publishing
For: Lin H, Wei C, Wang G, Chen H, Lin L, Ni M, Chen J, Zhuo S. Automated classification of hepatocellular carcinoma differentiation using multiphoton microscopy and deep learning. J Biophotonics 2019;12:e201800435. [PMID: 30868728 DOI: 10.1002/jbio.201800435] [Cited by in Crossref: 10] [Cited by in F6Publishing: 14] [Article Influence: 3.3] [Reference Citation Analysis]
Number Citing Articles
1 Pradhan P, Guo S, Ryabchykov O, Popp J, Bocklitz TW. Deep learning a boon for biophotonics? J Biophotonics 2020;13. [DOI: 10.1002/jbio.201960186] [Cited by in Crossref: 13] [Cited by in F6Publishing: 11] [Article Influence: 6.5] [Reference Citation Analysis]
2 Wang R, He Y, Yao C, Wang S, Xue Y, Zhang Z, Wang J, Liu X. Classification and Segmentation of Hyperspectral Data of Hepatocellular Carcinoma Samples Using 1-D Convolutional Neural Network. Cytometry A. 2020;97:31-38. [PMID: 31403260 DOI: 10.1002/cyto.a.23871] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
3 Huttunen MJ, Hristu R, Dumitru A, Floroiu I, Costache M, Stanciu SG. Multiphoton microscopy of the dermoepidermal junction and automated identification of dysplastic tissues with deep learning. Biomed Opt Express 2020;11:186-99. [PMID: 32010509 DOI: 10.1364/BOE.11.000186] [Cited by in Crossref: 9] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
4 Chen M, Zhang B, Topatana W, Cao J, Zhu H, Juengpanich S, Mao Q, Yu H, Cai X. Classification and mutation prediction based on histopathology H&E images in liver cancer using deep learning. NPJ Precis Oncol. 2020;4:14. [PMID: 32550270 DOI: 10.1038/s41698-020-0120-3] [Cited by in Crossref: 20] [Cited by in F6Publishing: 24] [Article Influence: 10.0] [Reference Citation Analysis]
5 Christou CD, Tsoulfas G. Role of three-dimensional printing and artificial intelligence in the management of hepatocellular carcinoma: Challenges and opportunities. World J Gastrointest Oncol 2022; 14(4): 765-793 [DOI: 10.4251/wjgo.v14.i4.765] [Reference Citation Analysis]
6 Chen W, Fu M, Zhang C, Xing Q, Zhou F, Lin M, Dong X, Huang J, Lin S, Hong M, Zheng Q, Pan J. Deep Learning-Based Universal Expert-Level Recognizing Pathological Images of Hepatocellular Carcinoma and Beyond. Front Med 2022;9:853261. [DOI: 10.3389/fmed.2022.853261] [Reference Citation Analysis]
7 Terradillos E, Saratxaga CL, Mattana S, Cicchi R, Pavone FS, Andraka N, Glover BJ, Arbide N, Velasco J, Etxezarraga MC, Picon A. Analysis on the Characterization of Multiphoton Microscopy Images for Malignant Neoplastic Colon Lesion Detection under Deep Learning Methods. J Pathol Inform 2021;12:27. [PMID: 34447607 DOI: 10.4103/jpi.jpi_113_20] [Reference Citation Analysis]
8 Balsano C, Alisi A, Brunetto MR, Invernizzi P, Burra P, Piscaglia F; Special Interest Group (SIG) Artificial Intelligence and Liver Diseases; Italian Association for the Study of the Liver (AISF). The application of artificial intelligence in hepatology: A systematic review. Dig Liver Dis 2021:S1590-8658(21)00317-0. [PMID: 34266794 DOI: 10.1016/j.dld.2021.06.011] [Reference Citation Analysis]
9 Matsumoto T, Niioka H, Kumamoto Y, Sato J, Inamori O, Nakao R, Harada Y, Konishi E, Otsuji E, Tanaka H, Miyake J, Takamatsu T. Deep-UV excitation fluorescence microscopy for detection of lymph node metastasis using deep neural network. Sci Rep. 2019;9:16912. [PMID: 31729459 DOI: 10.1038/s41598-019-53405-w] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
10 Cai S, Tian Y, Lui H, Zeng H, Wu Y, Chen G. Dense-UNet: a novel multiphoton in vivo cellular image segmentation model based on a convolutional neural network. Quant Imaging Med Surg 2020;10:1275-85. [PMID: 32550136 DOI: 10.21037/qims-19-1090] [Cited by in Crossref: 6] [Cited by in F6Publishing: 9] [Article Influence: 3.0] [Reference Citation Analysis]
11 König TT, Goedeke J, Muensterer OJ. Multiphoton microscopy in surgical oncology- a systematic review and guide for clinical translatability. Surg Oncol 2019;31:119-31. [PMID: 31654957 DOI: 10.1016/j.suronc.2019.10.011] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
12 Solovyev R, Kalinin AA, Gabruseva T. 3D convolutional neural networks for stalled brain capillary detection. Comput Biol Med 2021;141:105089. [PMID: 34920160 DOI: 10.1016/j.compbiomed.2021.105089] [Reference Citation Analysis]
13 Jain D, Torres R, Celli R, Koelmel J, Charkoftaki G, Vasiliou V. Evolution of the liver biopsy and its future. Transl Gastroenterol Hepatol 2021;6:20. [PMID: 33824924 DOI: 10.21037/tgh.2020.04.01] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
14 Menegotto AB, Becker CDL, Cazella SC. Computer-aided diagnosis of hepatocellular carcinoma fusing imaging and structured health data. Health Inf Sci Syst 2021;9:20. [PMID: 33968399 DOI: 10.1007/s13755-021-00151-x] [Reference Citation Analysis]
15 Ahn JC, Qureshi TA, Singal AG, Li D, Yang JD. Deep learning in hepatocellular carcinoma: Current status and future perspectives. World J Hepatol 2021; 13(12): 2039-2051 [DOI: 10.4254/wjh.v13.i12.2039] [Reference Citation Analysis]
16 Zherebtsov E, Zajnulina M, Kandurova K, Potapova E, Dremin V, Mamoshin A, Sokolovski S, Dunaev A, Rafailov EU. Machine Learning Aided Photonic Diagnostic System for Minimally Invasive Optically Guided Surgery in the Hepatoduodenal Area. Diagnostics (Basel) 2020;10:E873. [PMID: 33121013 DOI: 10.3390/diagnostics10110873] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
17 Hong D, Zheng YY, Xin Y, Sun L, Yang H, Lin MY, Liu C, Li BN, Zhang ZW, Zhuang J, Qian MY, Wang SS. Genetic syndromes screening by facial recognition technology: VGG-16 screening model construction and evaluation. Orphanet J Rare Dis 2021;16:344. [PMID: 34344442 DOI: 10.1186/s13023-021-01979-y] [Reference Citation Analysis]
18 Lin H, Fan T, Sui J, Wang G, Chen J, Zhuo S, Zhang H. Recent advances in multiphoton microscopy combined with nanomaterials in the field of disease evolution and clinical applications to liver cancer. Nanoscale 2019;11:19619-35. [PMID: 31599299 DOI: 10.1039/c9nr04902a] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 2.3] [Reference Citation Analysis]