Rapid identification of slow healing wounds

Volume: 24, Issue: 1, Pages: 181 - 188
Published: Jan 1, 2016
Abstract
Chronic nonhealing wounds have a prevalence of 2% in the United States, and cost an estimated $50 billion annually. Accurate stratification of wounds for risk of slow healing may help guide treatment and referral decisions. We have applied modern machine learning methods and feature engineering to develop a predictive model for delayed wound healing that uses information collected during routine care in outpatient wound care centers. Patient and...
Paper Details
Title
Rapid identification of slow healing wounds
Published Date
Jan 1, 2016
Volume
24
Issue
1
Pages
181 - 188
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.