Continuous updating of individual headache forecasting models using Bayesian methods.

ABSTRACT:

Objective

To illustrate the benefits of deploying individual headache forecasting models using continuous updating with Bayesian methods.

Background

The ability to reliably forecast headache attacks within an individual over time would enhance the study of attacks and allow preemptive treatment. However, deploying a suitable forecasting model in a clinical setting will likely involve several unique challenges related to heterogeneity in the predictor weights, limited or sparse data, and the need for a quick "warm-up." The use of Bayesian methods offers solutions to each of these specific challenges.

Methods

This was a post hoc analysis of a cohort study of individuals with episodic migraine attacks. Individuals completed daily diaries that allowed the estimation of se

SUBMITTER: Houle TT 

PROVIDER: S-EPMC8672809 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature