Automated detection of chronic kidney disease using higher-order features and elongated quinary patterns from B-mode ultrasound images-Reference-Cited by-同舟云学术

Automated detection of chronic kidney disease using higher-order features and elongated quinary patterns from B-mode ultrasound images

Published:2019-01-18 Issue:15 Volume:32 Page:11163-11172
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Acharya U. Rajendra^ORCID,Meiburger Kristen M.,Koh Joel En Wei,Hagiwara Yuki,Oh Shu Lih,Leong Sook Sam,Ciaccio Edward J.,Wong Jeannie Hsiu Ding,Shah Mohammad Nazri Md,Molinari Filippo,Ng Kwan Hoong

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/article/10.1007/s00521-019-04025-y/fulltext.html

Reference47 articles.

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2. Clinical Practice Guidelines-Management of chronic kidney disease in adults (2011). www.acadmed.org.my/view_file.cfm?fileid=497 . Accessed 16 Jan 2019

3. Remer EM, Papanicolaou N, Casalino DD, Bishoff JT, Blaufox MD, Coursey CA, Dighe M, Eberhardt SC, Goldfarb S, Harvin HJ, Heilbrun ME, Leyendecker JR, Nikolaidis P, Oto A, Preminger GM, Raman SS, Sheth S, Vikram R, Weinfeld RM (2014) ACR appropriateness criteria® on renal failure. Am J Med 127(11):1041–1048.e1

4. Fiorini F, Barozzi L (2007) The role of ultrasonography in the study of medical nephropathy. J Ultrasound 10(4):161–167

5. Norouzi J, Yadollahpour A, Mirbagheri SA, Mazdeh MM, Hosseini SA (2016) Predicting renal failure progression in chronic kidney disease using integrated intelligent fuzzy expert system. Comput Math Methods Med 2016:1–9

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