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Evidence

Use of Machine Learning Techniques in the Development and Refinement of a Predictive Model for Early Diagnosis of Ankylosing Spondylitis

Date: 07/16/2019

Journal: Clinical Rheumatology

Date published: May 2019

Authors: Atul Deodhar, Martin Rozycki, Cody Garges, Oodaye Shukla, Theresa Arndt, Tara Grabowsky, and Yujin Park

Objectives:

  • To develop a predictive mathematical model for the early identification of ankylosing spondylitis (AS) based on the medical and pharmacy claims history of patients with and without AS.

Conclusions:

  • Model A/B performed better than a clinically based model in predicting a diagnosis of AS among patients in a large claims database; its use may contribute to early recognition of AS and a timely diagnosis.

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