Integration of Artificial Intelligence (AI), Virtual/Augmented Reality (VR/AR) and Machine Learning (ML) in Clinical Practice: Patient Care, Clinician–Patient Interaction, and Clinical Decision-Making

A Special Issue of Healthcare (ISSN 2227-9032) belonging to the section "Artificial Intelligence in Healthcare".

Deadline for manuscript submissions: 1 September 2027 | Viewed by 1205

Editors


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Guest Editor
Faculty of Computer Science, Dalhousie University, 6050 University Avenue, P.O. BOX 15000, Halifax, NS B3H 4R2, Canada
Interests: human-centered AI; user-adaptive systems; persuasive technologies; dynamic user modeling; intervention design; digital health

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Guest Editor Assistant
Faculty of Computer Science, Dalhousie University, 6050 University Avenue, P.O. BOX 15000, Halifax, NS B3H 4R2, Canada
Interests: human-centered AI; digital health; human–computer interaction

Special Issue Information

Dear Colleagues,

The potential of Artificial Intelligence (AI), Virtual Reality/Augmented Reality (VR/AR), and Machine Learning (ML) technologies to transform clinical practice cannot be over-emphasized. These technologies provide useful tools for diagnostic support, prediction analytics, and individualized treatment planning, enabling clinicians to make more informed and timely decisions. For example, VR/AR provides comprehensive solutions to medical education, rehabilitation therapy, and patient contact, thereby enhancing communication between patients and clinicians. All of these technologies have been effective in real-world settings, but their implementation in clinical practice has remained controversial to date. Given the limited clinical evidence of potential for VR/AR, AI, and ML to enhance patient care, rehabilitation, and doctor–patient relationships, this Special Issue seeks to gather innovative contributions from the research community.

This Special Issue invites original research, systematic reviews, and case studies on the integration of AI, VR/AR, and ML in clinical environments. Topics can range from physician support systems, patient-centered applications, education in medicine, and clinical decision-making to the ethical considerations involved in introducing these technologies. Overall, the proposed Special Issue aims to bring together interdisciplinary perspectives to highlight innovations that can transform the provision of healthcare, improve patient outcomes, and empower medical professionals in practice.

Dr. Oladapo Oyebode
Guest Editor

Dr. Grace Ataguba
Guest Editor Assistant

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Keywords

  • artificial intelligence
  • virtual reality
  • augmented reality
  • machine learning
  • clinical applications
  • clinical decision-making
  • diagnosis
  • doctor–patient interaction
  • interventions

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Published Papers (2 papers)

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Research

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28 pages, 2766 KB  
Article
An Experimental Study on the Effectiveness and Usefulness of 360° Virtual Reality Simulation in Korean Medical Education: A Pilot Study
by Hyun-Kyung Sung, Yongtaek Oh, Mikyung Kim, Eun-Jin Kim, Ju-Hee Lee, Yejin Han and Namin Shin
Healthcare 2026, 14(10), 1426; https://doi.org/10.3390/healthcare14101426 - 21 May 2026
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Abstract
Background: Virtual reality (VR) simulations provide immersive, interactive learning environments that can support clinical skill development in medical education. However, evidence for its application in Korean medical education remains limited. This pilot study aimed to develop and evaluate HaniE-VR1, a 360° VR simulation [...] Read more.
Background: Virtual reality (VR) simulations provide immersive, interactive learning environments that can support clinical skill development in medical education. However, evidence for its application in Korean medical education remains limited. This pilot study aimed to develop and evaluate HaniE-VR1, a 360° VR simulation program designed to teach ultrasound-guided pharmacopuncture. Methods: A one-group pre–post experimental design was used with 60 undergraduate students from the College of Korean Medicine (pre-intervention n = 60; post-intervention n = 59, due to one missing post-survey response). The primary outcomes were changes in self-efficacy (MASS) and ultrasound skill-related performance (OSAUS). Secondary outcomes included VR awareness, usability, satisfaction, presence, and cognitive load. Participants completed a VR-based training session using a Meta Quest 3 headset. Effect sizes (Cohen’s d) were calculated for pre–post comparisons. Statistical significance was set at p < 0.05. Results: Post-intervention findings showed significant improvements in self-efficacy (MASS: 3.21 ± 0.51 to 3.54 ± 0.61, p < 0.001, d = 0.66) and ultrasound skill performance (OSAUS: 2.66 ± 0.73 to 3.54 ± 0.71, p < 0.001, d = 1.16). VR awareness also improved significantly (4.33 ± 0.66 to 4.76 ± 0.56, p < 0.001, d = 0.65). Participants reported acceptable usability (SUS = 69.49) and high satisfaction (4.51 ± 0.56), confidence (4.32 ± 0.53), and presence (4.40 ± 0.65). Cognitive load and simulator sickness were minimal. Conclusions: The HaniE-VR1 program was associated with improvements in perceived clinical competence, self-efficacy, and learning satisfaction, demonstrating acceptable usability and preliminary educational potential. VR simulations represent a feasible, safe, and engaging approach for integrating experiential learning into Korean medical curricula. Given the exploratory nature of this pilot study, findings should be interpreted with caution, and future controlled research is warranted. Full article
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24 pages, 1868 KB  
Systematic Review
Computer-Based Simulation Technologies in Pediatric Cardiovascular Diseases: A Systematic Review of Applications and Outcomes
by Arezoo Abasi, Haleh Ayatollahi and Amirhossein Amirzadeh
Healthcare 2026, 14(18), 3086; https://doi.org/10.3390/healthcare14183086 (registering DOI) - 19 Sep 2026
Abstract
Introduction: Computer-based simulation technologies, including virtual reality (VR), augmented reality (AR), mixed reality (MR), and three-dimensional (3D) modeling, are increasingly used in pediatric cardiovascular care. Despite growing adoption of these technologies, no comprehensive synthesis across VR, AR, MR, and 3D modeling modalities [...] Read more.
Introduction: Computer-based simulation technologies, including virtual reality (VR), augmented reality (AR), mixed reality (MR), and three-dimensional (3D) modeling, are increasingly used in pediatric cardiovascular care. Despite growing adoption of these technologies, no comprehensive synthesis across VR, AR, MR, and 3D modeling modalities exists for pediatric cardiovascular care. Objective: This review aimed to synthesize evidence regarding the applications and outcomes of computer-based simulation technologies in pediatric cardiovascular diseases. Methods: A systematic review was conducted by searching nine databases (PubMed, Web of Science, Scopus, Ovid, the Cochrane Library, IEEE Xplore, ProQuest, CINAHL, and EBSCO Host) for eligible studies published up to 1 September 2025. Thirty-six studies were included and appraised using the Mixed Methods Appraisal Tool (MMAT), the Critical Appraisal Skills Programme (CASP) checklist, and the ROBINS-I tool. Substantial clinical and methodological heterogeneity precluded meta-analysis. Results: VR was the most frequently used modality (n = 14), followed by 3D modeling (n = 8), multimodal approaches (n = 8), MR (n = 6), and AR (n = 3). This technology was mainly used for congenital heart defects (n = 18). MR holography improved diagnostic accuracy for complex anomalies (95.5% vs. 89.7%); VR-based surgical plans aligned better with the real surgery than did 2D imaging plans (80% vs. 66%); VR was preferred over 3D-printed models by 87% of participants (8.5/10 vs. 6.3/10 for anatomical understanding); and VR curricula (Stanford Virtual Heart) significantly increased CHD knowledge scores among students and residents (p < 0.05). However, this evidence was predominantly derived from small, single-center observational studies, with barriers including hardware limitations and limited long-term outcome data. Conclusions: Computer-based simulation technologies show considerable potential for surgical planning, diagnostic assessment, and education in pediatric cardiovascular diseases. They can be used as complementary tools rather than replacements for standard imaging or clinical judgment. While VR and 3D modeling show promise for surgical planning and education, multicenter comparative studies with standardized outcomes and cost-effectiveness analyses are essential before routine clinical implementation. Full article
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