Download from app store
We have detected that you are using an Ad Blocker.
PracticeUpdate is free to end users but we rely on advertising to fund our site. Please consider supporting PracticeUpdate by whitelisting us in your ad blocker.
We have sent a message to the email address you have provided, . If this email is not correct, please update your settings with your correct address.
The email address you provided during registration, , does not appear to be valid. Please update your settings with a valid address before to continue using PracticeUpdate.
Please provide your AHPRA Number to ensure that you are given the correct level of access to our site.
Sign in
Join now

In an effort to better serve our users, we have streamlined our content offering. As a result, we no longer publish new content or update existing content in Urology. Visit the 'Content & Subscriptions' tab of your Settings page at any time to update your Dashboard or Newsletter Subscription preferences to continue to see news and information that interests you most.

featured
Published in Urology

Journal Scan / Research · March 18, 2019

Using a Machine Learning Model to Identify Children Most Likely to Benefit From VCUG Following Initial Febrile UTI

The Journal of Urology

 

 Save  Recommend
 Share

Additional Info

Disclosure statements are available on the authors' profiles:

Joshua Cohn MD, FPMRS

Craig Peters MD, FAAP, FACS

The Journal of Urology
Targeted Workup After Initial Febrile Urinary Tract Infection: Using a Novel Machine Learning Model to Identify Children Most Likely to Benefit From VCUG
J Urol 2019 Feb 15;[EPub Ahead of Print], D Bertsimas, J Dunn, M Li, D Zhuo, C Estrada, C Nelson, HHS Wang

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

Further Reading

Recently Updated