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BRIEF RESEARCH REPORT article

Front. Artif. Intell.
Sec. Medicine and Public Health
Volume 7 - 2024 | doi: 10.3389/frai.2024.1424371
This article is part of the Research Topic Data Science and Digital Health Technologies for Personalized Healthcare View all articles

A brief reference to AI-driven audible reality (AuRa) in open world: potential, applications, and evaluation

Provisionally accepted
  • SRH Hochschule Heidelberg, Heidelberg, Germany

The final, formatted version of the article will be published soon.

    Recent developments on artificial intelligence (AI) and machine learning (ML) techniques are expected to have significant impact on public health in several ways. Indeed, modern AI/ML methods have been applied on multiple occasions on topics ranging from drug discovery and disease diagnostics to personalized medicine, medical imaging, and healthcare operations. While such developments may improve several quality-of-life aspects (such as access to health services and education), it is important considering that some individuals may face more challenges, particularly in extreme or emergency situations. In this work, we focus on utilizing AI/ML components to support scenarios when visual impairment or other limitations hinder the ability to interpret the world in this way. Specifically, we discuss the potential and the feasibility of automatically transferring key visual information into audio communication, in different languages and in real-time -a setting which we name 'audible reality' (AuRa). We provide a short guide to practical options currently available for implementing similar solutions and summarize key aspects for evaluating their scope. Finally, we discuss diverse settings and functionalities that AuRA applications could have in terms of broader impact, from a social and public health context, and invite the community to further such digital solutions and perspectives soon.

    Keywords: Digital Health, Public Health, object recognition, Text to speech, visual aid companion, vision impairment, real world decision support, biomedicine and healthcare informatics

    Received: 27 Apr 2024; Accepted: 04 Oct 2024.

    Copyright: © 2024 Ates, Pandey and Soldatos. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Theodoros Soldatos, SRH Hochschule Heidelberg, Heidelberg, Germany

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.