Development of a personalized diagnostic model for kidney stone disease tailored to acute care by integrating large clinical, demographics and laboratory data: the diagnostic acute care algorithm - kidney stones (DACA-KS)-Reference-Cited by-同舟云学术

Development of a personalized diagnostic model for kidney stone disease tailored to acute care by integrating large clinical, demographics and laboratory data: the diagnostic acute care algorithm - kidney stones (DACA-KS)

Published:2018-08-17 Issue:1 Volume:18 Page:
ISSN:1472-6947
Container-title:BMC Medical Informatics and Decision Making
language:en
Short-container-title:BMC Med Inform Decis Mak

Author:

Chen Zhaoyi^ORCID,Bird Victoria Y.,Ruchi Rupam,Segal Mark S.,Bian Jiang,Khan Saeed R.,Elie Marie-Carmelle,Prosperi Mattia

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Health Policy,Computer Science Applications

Link

http://link.springer.com/content/pdf/10.1186/s12911-018-0652-4.pdf

Reference39 articles.

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2. Antonelli JA, Maalouf NM, Pearle MS, Lotan Y. Use of the National Health and nutrition examination survey to calculate the impact of obesity and diabetes on cost and prevalence of urolithiasis in 2030. Eur Urol. 2014 Oct;66(4):724–9.

3. Morgan MS, Pearle MS. Medical management of renal stones. BMJ. 2016 Mar 14;352:i52.

4. Rule AD, Bergstralh EJ, Melton LJ 3rd, Li X, Weaver AL, Lieske JC. Kidney stones and the risk for chronic kidney disease. Clin J Am Soc Nephrol. 2009 Apr;4(4):804–11.

5. Graham A, Luber S, Wolfson AB. Urolithiasis in the emergency department. Emerg Med Clin North Am. 2011 Aug;29(3):519–38.

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