Towards Understanding the Usability Attributes of AI-Enabled eHealth Mobile Applications.

Mohammad J Algahamdi ,Abdel Saeed Alzahrani ,Adel Saeed Alzahrani,Ryan Alturki,Mohammad J Alghamdi,Valerie Gay,Ayush Dogra

doi:10.1155/2021/5313027

Mohammad J Algahamdi , Abdel Saeed Alzahrani + Show 5 more

Open Access

https://doi.org/10.1155/2021/5313027

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Abstract

Mobile application (app) use is increasingly becoming an essential part of our daily lives. Due to their significant usefulness, people rely on them to perform multiple tasks seamlessly in almost all aspects of everyday life. Similarly, there has been immense progress in artificial intelligence (AI) technology, especially deep learning, computer vision, natural language processing, and robotics. These technologies are now actively being implemented in smartphone apps and healthcare, providing multiple healthcare services. However, several factors affect the usefulness of mobile healthcare apps, and usability is an important one. There are various healthcare apps developed for each specific task, and the success of these apps depends on their performance. This study presents a systematic review of the existing apps and discusses their usability attributes. It highlights the usability models, outlines, and guidelines proposed in previous research for designing apps with improved usability characteristics. Thirty-nine research articles were reviewed and examined to identify the usability attributes, framework, and app design conducted. The results showed that satisfaction, efficiency, and learnability are the most important usability attributes to consider when designing eHealth mobile apps. Surprisingly, other significant attributes for healthcare apps, such as privacy and security, were not among the most indicated attributes in the studies.

Highlights

Some studies tested the usability attributes of a single application, while others compared various mobile applications with an emphasis on certain attributes. e major purpose of this study is to identify the user’s satisfaction, learnability, and memorability, on this mobile app
Machine learning supports mobile applications to predict the same pattern entered by the user, and it constantly relies on those patterns
Is study demonstrated the various usability attributes that end users want in AI-enabled mobile applications

Summary

Selected Literature

AI software and devices have the ability to automatically learn from real-world environments and can improve in performance over time [12, 15]. is characteristic of AI software distinguishes it from other software used in healthcare and presents novel monitoring challenges. Is characteristic of AI software distinguishes it from other software used in healthcare and presents novel monitoring challenges. E aim of an AI-based eHealth application is to develop a healthcare system strengthened by a series of approaches based on the mining of knowledge accumulated in the large amount of data that the system generates about the patients [27]. In an AI-enabled eHealth system, data collected by wearable sensors and devices can be conveniently treated to be sent and integrated into the patient’s medical history, which is stored in the hospital’s server system or computing cloud [28, 29]. AI-based eHealth applications aim to integrate knowledge about a given disease into an algorithmic set.

Data Extraction and Categorisation

Results and Discussion

Conclusions