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A Data Analytics Strategy to Identify mHealth Apps Quality Improvements. A Case Study

Published: 26 October 2021 Publication History

Abstract

This study uses a dataset that comes from the employment of the Mobile App Rating Scale (MARS) model. The dataset comprehends 565 Spanish Language Apps for People with special skills, published during the last twenty years. This work aims to identify influential features to improve mHealth apps quality using a data analytics strategy that integrates the MARS model, Principal Components Analysis (PCA), and Genetic Algorithms (GA). The results show that it is feasible to find specific characteristics that could improve the apps. The process used involves a practical contribution conducted to the stakeholders promoting the enhancement of the quality of life using mHealth approach.

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cover image ACM Other conferences
ICMHI '21: Proceedings of the 5th International Conference on Medical and Health Informatics
May 2021
347 pages
ISBN:9781450389846
DOI:10.1145/3472813
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 26 October 2021

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Author Tags

  1. Genetic Algorithms
  2. MARS
  3. Principal Components
  4. mHealth Apps

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