IDEAS home Printed from https://ideas.repec.org/h/spr/conchp/978-3-032-13458-5_15.html

Exploring the Convergence of XR and AI Potential in Healthcare: The TOMMI Project Case Study

In: Artificial Intelligence and Networks for a Sustainable Future

Author

Listed:
  • Isabella Corvino

    (Università degli studi di Perugia, Perugia piazza Ermini)

  • Valentino Megale

    (Softcare, Studios Srls)

Abstract

In recent years, the AI-powered revolution in healthcare has been met with enthusiastic praise. Many innovative projects aim to reshape the healthcare experience by leveraging AI to enhance tools that provide personalized care, utilizing data that is quickly collected and analyzed. Possibilities for AI integration are being analyzed, in the case of TOMMI, a product by Softcare Studios, a virtual reality (VR) experience designed for pediatric patients. The relational environment of the patients, often complicated by a level of stress so high it can interfere with their ability to manage or even accept treatment, serves as a key setting for the experimentation of new tools. There is here an interesting argument to be made: even though highly technological, non-pharmacological solutions represent a radical turning point in the perception of the body and in the creation of more inclusive care environments with fewer side effects compared to the use of medications, it could be argued that, in this case, their success negates the same Cartesian dualism body/soul that still powerfully shapes mainstream discourses and from which they issue, as it shows a deep, intimate connection between them which can be tapped through imaginal, non-rational instances the aim is to explore the effects of new technologies, particularly AI and VR, on scientific progress and the sociological and psychological aspects of healthcare.

Suggested Citation

  • Isabella Corvino & Valentino Megale, 2026. "Exploring the Convergence of XR and AI Potential in Healthcare: The TOMMI Project Case Study," Contributions to Economics, in: Francesca Greco & Andrea Fronzetti Colladon & Peter A. Gloor (ed.), Artificial Intelligence and Networks for a Sustainable Future, pages 267-279, Springer.
  • Handle: RePEc:spr:conchp:978-3-032-13458-5_15
    DOI: 10.1007/978-3-032-13458-5_15
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:conchp:978-3-032-13458-5_15. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.