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For: Acharya UR, Raghavendra U, Koh JEW, Meiburger KM, Ciaccio EJ, Hagiwara Y, Molinari F, Leong WL, Vijayananthan A, Yaakup NA, Fabell MKBM, Yeong CH. Automated detection and classification of liver fibrosis stages using contourlet transform and nonlinear features. Computer Methods and Programs in Biomedicine 2018;166:91-8. [DOI: 10.1016/j.cmpb.2018.10.006] [Cited by in Crossref: 10] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
Number Citing Articles
1 Feng X, Chen X, Dong C, Liu Y, Liu Z, Ding R, Huang Q. Multi-scale information with attention integration for classification of liver fibrosis in B-mode US image. Comput Methods Programs Biomed 2021;215:106598. [PMID: 34986432 DOI: 10.1016/j.cmpb.2021.106598] [Reference Citation Analysis]
2 Wang X, Qian H, Ciaccio EJ, Lewis SK, Bhagat G, Green PH, Xu S, Huang L, Gao R, Liu Y. Celiac disease diagnosis from videocapsule endoscopy images with residual learning and deep feature extraction. Comput Methods Programs Biomed 2020;187:105236. [PMID: 31786452 DOI: 10.1016/j.cmpb.2019.105236] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
3 Maheshwari S, Sharma RR, Kumar M. LBP-based information assisted intelligent system for COVID-19 identification. Comput Biol Med 2021;134:104453. [PMID: 33957343 DOI: 10.1016/j.compbiomed.2021.104453] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Diab A, Boudaoud S, Karlsson B, Marque C. Performance comparison of coupling-evaluation methods in discriminating between pregnancy and labor EHG signals. Comput Biol Med 2021;132:104308. [PMID: 33711558 DOI: 10.1016/j.compbiomed.2021.104308] [Reference Citation Analysis]
5 Nguyen PA, Jack Li YC. Artificial Intelligence in Clinical Implications. Comput Methods Programs Biomed 2018;166:A1. [PMID: 30415724 DOI: 10.1016/j.cmpb.2018.10.022] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]
6 Xue LY, Jiang ZY, Fu TT, Wang QM, Zhu YL, Dai M, Wang WP, Yu JH, Ding H. Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis.Eur Radiol. 2020;30:2973-2983. [PMID: 31965257 DOI: 10.1007/s00330-019-06595-w] [Cited by in Crossref: 16] [Cited by in F6Publishing: 14] [Article Influence: 8.0] [Reference Citation Analysis]
7 Koh JEW, Raghavendra U, Gudigar A, Ping OC, Molinari F, Mishra S, Mathavan S, Raman R, Acharya UR. A novel hybrid approach for automated detection of retinal detachment using ultrasound images. Comput Biol Med 2020;120:103704. [PMID: 32250849 DOI: 10.1016/j.compbiomed.2020.103704] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
8 Chen CI, Chen TB, Lu NH, Du WC, Liang CY, Liu KI, Hsu SY, Lin LW, Huang YH. Classification for liver ultrasound tomography by posterior attenuation correction with a phantom study. Proc Inst Mech Eng H 2019;233:1100-12. [PMID: 31441386 DOI: 10.1177/0954411919871123] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]