Machine-learning based analysis of mobile apps for people with Alzheimer's disease

Roobaea Alroobaea, Mariem Haoues, Saeed Rubaiee, Anas Ahmed, Fahad Almansour

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Although Alzheimer's is a progressive disease, individuals with Alzheimer's can have a normal life if they manage their lifestyle correctly and control the disease's symptoms. Currently, mobile apps provide a helpful solution for disease management assistance outside hospitals. Reviewing mobile apps users’ feedback allows developers to better understand patients’ needs and guarantee their satisfaction. In this paper, we analyze user reviews suggested on 10 selected mobile apps for individuals with Alzheimer's. A total of 1675 user reviews have been collected, including positive and negative opinions. This analysis has been performed based on machine learning and natural language processing techniques. The best performance was provided by the support vector machine classifier with accuracy equal to 99.43% in classifying user reviews into positive and negative reviews. The results of this analysis showed that users are not satisfied with the quality of the mobile apps available for people with Alzheimer's, especially the usability.

Original languageEnglish
Pages (from-to)126-133
Number of pages8
JournalSSRG International Journal of Engineering Trends and Technology
Volume69
Issue number2
DOIs
StatePublished - Feb 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 Seventh Sense Research Group®.

Keywords

  • Alzheimer's disease
  • Machine learning
  • Mobile apps
  • Natural language processing
  • Opinion analysis

ASJC Scopus subject areas

  • General Engineering

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