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eXtended Reality and Artificial Intelligence in Medicine and Rehabilitation

Author

Listed:
  • Tomas Krilavičius

    (Vytautas Magnus University)

  • Lucio Tommaso De Paolis

    (University of Salento)

  • Valerio De Luca

    (University of Salento)

  • Josef Spjut

    (NVIDIA)

Abstract

This special issue focuses on the application of eXtended Reality (XR) technologies—comprising Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR)—and Artificial Intelligence (AI) in the fields of medicine and rehabilitation. AR provides support in minimally invasive surgery, where it visualises internal anatomical structures on the patient’s body and provides real-time feedback to improve accuracy, keep the surgeon’s attention and reduce the risk of errors. Furthermore, XR technologies can be used to develop applications for pre-operative planning or for training surgeons through serious games. AI finds applications both in medical image processing, for the recognition of anatomical structures and the reconstruction of 3D models, and in the analysis of biological data for patient monitoring and disease diagnosis. In rehabilitation, XR and AI can enable personalised therapy plans, increase patient engagement through immersive environments and provide real-time feedback to improve recovery outcomes. The papers in this special issue deal with rehabilitation through serious games, AI-enhanced XR applications for healthcare, digital twins and the analysis of bio/neuro-adaptive signals.

Suggested Citation

  • Tomas Krilavičius & Lucio Tommaso De Paolis & Valerio De Luca & Josef Spjut, 2025. "eXtended Reality and Artificial Intelligence in Medicine and Rehabilitation," Information Systems Frontiers, Springer, vol. 27(1), pages 1-6, February.
    • Handle: RePEc:spr:infosf:v:27:y:2025:i:1:d:10.1007_s10796-025-10580-8
    DOI: 10.1007/s10796-025-10580-8
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    References listed on IDEAS

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    1. Laura Cercenelli & Nicolas Emiliani & Chiara Gulotta & Mirko Bevini & Giovanni Badiali & Emanuela Marcelli, 2025. "Augmented Reality to Assist in the Diagnosis of Temporomandibular Joint Alterations," Information Systems Frontiers, Springer, vol. 27(1), pages 33-49, February.
    2. Francesca Angelone & Federica Kiyomi Ciliberti & Giovanni Paolo Tobia & Halldór Jónsson & Alfonso Maria Ponsiglione & Magnus Kjartan Gislason & Francesco Tortorella & Francesco Amato & Paolo Gargiulo, 2025. "Innovative Diagnostic Approaches for Predicting Knee Cartilage Degeneration in Osteoarthritis Patients: A Radiomics-Based Study," Information Systems Frontiers, Springer, vol. 27(1), pages 51-73, February.
    3. Aaron Lawson McLean & Anna C. Lawson McLean, 2024. "Immersive Simulations in Surgical Training: Analyzing the Interplay Between Virtual and Real-World Environments," Simulation & Gaming, , vol. 55(6), pages 1103-1123, December.
    4. Bianca-Ştefania Munteanu & Alexandra Murariu & Mǎrioara Nichitean & Luminiţa-Gabriela Pitac & Laura Dioşan, 2025. "Value of Original and Generated Ultrasound Data Towards Training Robust Classifiers for Breast Cancer Identification," Information Systems Frontiers, Springer, vol. 27(1), pages 75-96, February.
    5. Giulia Pellegrino & Massimiliano Gervasi & Mario Angelelli & Angelo Corallo, 2025. "A Conceptual Framework for Digital Twin in Healthcare: Evidence from a Systematic Meta-Review," Information Systems Frontiers, Springer, vol. 27(1), pages 7-32, February.
    6. Zhuo Chen & Chuda Xiao & Yang Liu & Haseeb Hassan & Dan Li & Jun Liu & Haoyu Li & Weiguo Xie & Wen Zhong & Bingding Huang, 2025. "Comprehensive 3D Analysis of the Renal System and Stones: Segmenting and Registering Non-Contrast and Contrast Computed Tomography Images," Information Systems Frontiers, Springer, vol. 27(1), pages 97-111, February.
    7. Joyce S.Y. Lau & Yuk Ming Tang & Grace Gao & Kenneth N.K. Fong & Billy C.L. So, 2025. "Development and Usability Testing of Virtual Reality (VR)-Based Reminiscence Therapy for People with Dementia," Information Systems Frontiers, Springer, vol. 27(1), pages 155-170, February.
    8. R. Rajesh, 2025. "A Grey Combined Prediction Model for Medical Treatment Risk Analysis during Pandemics," Information Systems Frontiers, Springer, vol. 27(1), pages 171-195, February.
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