Utilizing Clinical Metadata to Predict High-Cost Complications and Treatment Response in IBD: Development of Clinical Decision Support Tools

Abstract

IBD is a costly and debilitating disease, significantly affecting quality of life. Our research plans are to generate easy to use, internet based tools (similar to a calculator) to determine which patient will go on to have costly disease over the next several years, and/or is unlikely to respond to traditional biologic therapies with anti-TNF medications. We propose using an already available IBD patient registry database which has been developed by the P.I. and the research team at UPMC/University of Pittsburgh.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2021
Accession Number
AD1190611

Entities

People

  • Claudia R. Rivers
  • David G. Binion

Organizations

  • University of Pittsburgh

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Bayesian Networks
  • Biological Factors
  • Biological Therapy
  • Blood
  • Colitis
  • Computers
  • Data Mining
  • Data Sets
  • Database Management Systems
  • Databases
  • Decision Support Systems
  • Dermatologic Agents
  • Health Services
  • Information Science
  • Machine Learning
  • Medical Personnel
  • Probabilistic Models
  • Relational Database Management Systems
  • Relational Databases
  • Supervised Machine Learning
  • Therapy
  • User Interface

Fields of Study

  • Medicine

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