Literature DB >> 32718516

Artificial Intelligence for Personalized Preventive Adolescent Healthcare.

Jonathan P Rowe1, James C Lester2.   

Abstract

Recent advances in artificial intelligence (AI) are creating new opportunities for personalizing technology-based health interventions to adolescents. This article provides a computer science perspective on how emerging AI technologies-intelligent learning environments, interactive narrative generation, user modeling, and adaptive coaching-can be utilized to model adolescent learning and engagement and deliver personalized support in adaptive health technologies. Many of these technologies have emerged from human-centered applications of AI in education, training, and entertainment. However, their application to improving healthcare, to date, has been comparatively limited. We illustrate the opportunities provided by AI-driven adaptive technologies for adolescent preventive healthcare by describing a vision of how future adolescent preventive health interventions might be delivered both inside and outside of the clinic. Key challenges posed by AI-driven health technologies are also presented, including issues of privacy, ethics, encoded bias, and integration into clinical workflows and adolescent lives. Examples of empirical findings about the effectiveness of AI technologies for user modeling and adaptive coaching are presented, which underscore their promise for application toward adolescent health. The article concludes with a brief discussion of future research directions for the field, which is well positioned to leverage AI to improve adolescent health and well-being.
Copyright © 2020. Published by Elsevier Inc.

Entities:  

Keywords:  Adaptive learning technologies; Adolescents; Artificial intelligence; Health information technology; Interactive narrative generation; Prevention; User modeling

Mesh:

Year:  2020        PMID: 32718516     DOI: 10.1016/j.jadohealth.2020.02.021

Source DB:  PubMed          Journal:  J Adolesc Health        ISSN: 1054-139X            Impact factor:   5.012


  4 in total

1.  Mitigating Issues With/of/for True Personalization.

Authors:  Harri Oinas-Kukkonen; Sami Pohjolainen; Eunice Agyei
Journal:  Front Artif Intell       Date:  2022-04-26

2.  Undergraduate Medical Students' and Interns' Knowledge and Perception of Artificial Intelligence in Medicine.

Authors:  Nisha Jha; Pathiyil Ravi Shankar; Mohammed Azmi Al-Betar; Rupesh Mukhia; Kabita Hada; Subish Palaian
Journal:  Adv Med Educ Pract       Date:  2022-08-23

3.  Bibliometric Analysis of Health Technology Research: 1990~2020.

Authors:  Xiaomei Luo; Yuduo Wu; Lina Niu; Lucheng Huang
Journal:  Int J Environ Res Public Health       Date:  2022-07-25       Impact factor: 4.614

4.  Using Technology to Improve the Health and Well-Being of Adolescents and Young Adults.

Authors:  Charles E Irwin
Journal:  J Adolesc Health       Date:  2020-08       Impact factor: 5.012

  4 in total

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