Viewpoint on Time Series and Interrupted Time Series Optimum Modeling for Predicting Arthritic Disease Outcomes.

Journal: Current rheumatology reports

PMID: 32435959

Abstract

PURPOSE OF REVIEW: The propose of this viewpoint is to improve or facilitate the clinical decision-making in the management/treatment strategies of arthritis patients through knowing, understanding, and having access to an interactive process allowing assessment of the patient disease outcome in the future.

Authors

Hossein Bonakdari

Department of Civil Engineering, Razi University, Kermanshah, Iran and Water and Wastewater Research Center, Razi University, Kermanshah, Iran E-mail: bonakdari@yahoo.com.
Jean-Pierre Pelletier

Osteoarthritis Research Unit, University of Montreal Hospital Research Centre (CRCHUM), Montreal, Quebec, Canada.
Johanne Martel-Pelletier

Osteoarthritis Research Unit, University of Montreal Hospital Research Centre (CRCHUM), Montreal, Quebec, Canada. jm@martelpelletier.ca.

Keywords

Arthritis Artificial Intelligence Humans Interrupted Time Series Analysis Linear Models Machine Learning Stochastic Processes

External Resources

View on PubMed Access via DOI PubMed (32435959)

Viewpoint on Time Series and Interrupted Time Series Optimum Modeling for Predicting Arthritic Disease Outcomes.

Abstract

Authors

Keywords

External Resources

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