EczemaPred: A computational framework for personalised prediction of eczema severity dynamics.

ABSTRACT:

Background

Atopic dermatitis (AD) is a chronic inflammatory skin disease leading to substantial quality of life impairment with heterogeneous treatment responses. People with AD would benefit from personalised treatment strategies, whose design requires predicting how AD severity evolves for each individual.

Objective

This study aims to develop a computational framework for personalised prediction of AD severity dynamics.

Methods

We introduced EczemaPred, a computational framework to predict patient-dependent dynamic evolution of AD severity using Bayesian state-space models that describe latent dynamics of AD severity items and how they are measured. We used EczemaPred to predict the dynamic evolution of validated patient-oriented scoring atopic dermatitis (PO-SCORAD

SUBMITTER: Hurault G 

PROVIDER: S-EPMC8967258 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature