BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Gao Y, Zhang ZD, Li S, Guo YT, Wu QY, Liu SH, Yang SJ, Ding L, Zhao BC, Lu Y. Deep neural network-assisted computed tomography diagnosis of metastatic lymph nodes from gastric cancer. Chin Med J (Engl). 2019;132:2804-2811. [PMID: 31856051 DOI: 10.1097/cm9.0000000000000532] [Cited by in Crossref: 16] [Cited by in F6Publishing: 13] [Article Influence: 8.0] [Reference Citation Analysis]
Number Citing Articles
1 Ramesh P, Karuppasamy R, Veerappapillai S. A review on recent advancements in diagnosis and classification of cancers using artificial intelligence. Biomedicine (Taipei) 2020;10:5-17. [PMID: 33854922 DOI: 10.37796/2211-8039.1012] [Reference Citation Analysis]
2 Zhao Y, Hu B, Wang Y, Yin X, Jiang Y, Zhu X. Identification of gastric cancer with convolutional neural networks: a systematic review. Multimed Tools Appl. [DOI: 10.1007/s11042-022-12258-8] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
3 Gao Y, Lu Y, Li S, Dai Y, Feng B, Han FH, Han JG, He JJ, Li XX, Lin GL, Liu Q, Wang GY, Wang Q, Wang ZN, Wang Z, Wu AW, Wu B, Yang YC, Yao HW, Zhang W, Zhou JP, Hao AM, Zhang ZT; Colorectal Surgery Group of the Surgery Branch in the Chinese Medical Association; Beihang University State Key Laboratory of Virtual Reality Technology and Systems. Chinese guideline for the application of rectal cancer staging recognition systems based on artificial intelligence platforms (2021 edition). Chin Med J (Engl) 2021;134:1261-3. [PMID: 34075899 DOI: 10.1097/CM9.0000000000001483] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Jeffrey Kuo C, Hsun Lin K, Weng W, Barman J, Huang C, Chiu C, Lee J, Hsu H. Complete fully automatic segmentation and 3-dimensional measurement of mediastinal lymph nodes for a new response evaluation criteria for solid tumors. Biocybernetics and Biomedical Engineering 2021;41:617-35. [DOI: 10.1016/j.bbe.2021.03.008] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Zheng Q, Yang L, Zeng B, Li J, Guo K, Liang Y, Liao G. Artificial intelligence performance in detecting tumor metastasis from medical radiology imaging: A systematic review and meta-analysis. EClinicalMedicine 2021;31:100669. [PMID: 33392486 DOI: 10.1016/j.eclinm.2020.100669] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
6 Kudou M, Kosuga T, Otsuji E. Artificial intelligence in gastrointestinal cancer: Recent advances and future perspectives. Artif Intell Gastroenterol 2020; 1(4): 71-85 [DOI: 10.35712/aig.v1.i4.71] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Cao B, Zhang KC, Wei B, Chen L. Status quo and future prospects of artificial neural network from the perspective of gastroenterologists. World J Gastroenterol 2021; 27(21): 2681-2709 [PMID: 34135549 DOI: 10.3748/wjg.v27.i21.2681] [Cited by in CrossRef: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Kinami S, Saito H, Takamura H. Significance of Lymph Node Metastasis in the Treatment of Gastric Cancer and Current Challenges in Determining the Extent of Metastasis. Front Oncol 2021;11:806162. [PMID: 35071010 DOI: 10.3389/fonc.2021.806162] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
9 Kröner PT, Engels MM, Glicksberg BS, Johnson KW, Mzaik O, van Hooft JE, Wallace MB, El-Serag HB, Krittanawong C. Artificial intelligence in gastroenterology: A state-of-the-art review. World J Gastroenterol 2021; 27(40): 6794-6824 [PMID: 34790008 DOI: 10.3748/wjg.v27.i40.6794] [Reference Citation Analysis]
10 Yakar M, Etiz D. Artificial intelligence in rectal cancer. Artif Intell Gastroenterol 2021; 2(2): 10-26 [DOI: 10.35712/aig.v2.i2.10] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
11 Yang R, Yan C, Lu S, Li J, Ji J, Yan R, Yuan F, Zhu Z, Yu Y. Tracking cancer lesions on surgical samples of gastric cancer by artificial intelligent algorithms. J Cancer 2021;12:6473-83. [PMID: 34659538 DOI: 10.7150/jca.63879] [Reference Citation Analysis]
12 Kim H, Lim Y, Seo S, Lee K, Kim J, Shin W. A Deep Recurrent Neural Network-Based Explainable Prediction Model for Progression from Atrophic Gastritis to Gastric Cancer. Applied Sciences 2021;11:6194. [DOI: 10.3390/app11136194] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
13 Qin Y, Deng Y, Jiang H, Hu N, Song B. Artificial Intelligence in the Imaging of Gastric Cancer: Current Applications and Future Direction. Front Oncol 2021;11:631686. [PMID: 34367946 DOI: 10.3389/fonc.2021.631686] [Reference Citation Analysis]
14 Niu PH, Zhao LL, Wu HL, Zhao DB, Chen YT. Artificial intelligence in gastric cancer: Application and future perspectives. World J Gastroenterol 2020; 26(36): 5408-5419 [PMID: 33024393 DOI: 10.3748/wjg.v26.i36.5408] [Cited by in CrossRef: 12] [Cited by in F6Publishing: 7] [Article Influence: 6.0] [Reference Citation Analysis]
15 Ao S, Wang Y, Song Q, Ye Y, Lyu G. Current status and future perspectives on neoadjuvant therapy in gastric cancer. Chin J Cancer Res 2021;33:181-92. [PMID: 34158738 DOI: 10.21147/j.issn.1000-9604.2021.02.06] [Reference Citation Analysis]
16 Meng X, Peng Y, Guo Y. An adaptive multi-scale network with nonorthogonal multi-union input for reducing false positive of lymph nodes. Biocybernetics and Biomedical Engineering 2021;41:265-77. [DOI: 10.1016/j.bbe.2021.01.005] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
17 Yang R, Yu Y. Artificial Convolutional Neural Network in Object Detection and Semantic Segmentation for Medical Imaging Analysis. Front Oncol 2021;11:638182. [PMID: 33768000 DOI: 10.3389/fonc.2021.638182] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
18 Yu C, Helwig EJ. Artificial intelligence in gastric cancer: a translational narrative review. Ann Transl Med 2021;9:269. [PMID: 33708896 DOI: 10.21037/atm-20-6337] [Reference Citation Analysis]
19 Wang WA, Dong P, Zhang A, Wang WJ, Guo CA, Wang J, Liu HB. Artificial intelligence: A new budding star in gastric cancer. Artif Intell Gastroenterol 2020; 1(4): 60-70 [DOI: 10.35712/aig.v1.i4.60] [Reference Citation Analysis]