Prediction of caregiver burden in amyotrophic lateral sclerosis: a machine learning approach using random forests applied to a cohort study.

ABSTRACT:

Objectives

Amyotrophic lateral sclerosis (ALS) is a rare neurodegenerative disease that is characterised by the rapid degeneration of upper and lower motor neurons and has a fatal trajectory 3-4 years from symptom onset. Due to the nature of the condition patients with ALS require the assistance of informal caregivers whose task is demanding and can lead to high feelings of burden. This study aims to predict caregiver burden and identify related features using machine learning techniques.

Design

This included demographic and socioeconomic information, quality of life, anxiety and depression questionnaires, for patients and carers, resource use of patients and clinical information. The method used for prediction was the Random forest algorithm.

Setting and participants

SUBMITTER: Antoniadi AM 

PROVIDER: S-EPMC7050406 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature