AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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2025
Koizumi, M.; Ohsuga, M.; Corchado, J. M.
Development and Assessment of a System to Help Students Improve Self-compassion Proceedings Article
In: R., Chinthaginjala; P., Sitek; N., Min-Allah; K., Matsui; S., Ossowski; S., Rodríguez (Ed.): Lect. Notes Networks Syst., pp. 43–52, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 23673370 (ISSN); 978-303182072-4 (ISBN).
Abstract | Links | BibTeX | Tags: Avatar, Generative adversarial networks, Generative AI, Health issues, Mental health, Self-compassion, Students, Training program, University students, Virtual avatar, Virtual environments, Virtual Reality, Virtual Space, Virtual spaces, Visual imagery
@inproceedings{koizumi_development_2025,
title = {Development and Assessment of a System to Help Students Improve Self-compassion},
author = {M. Koizumi and M. Ohsuga and J. M. Corchado},
editor = {Chinthaginjala R. and Sitek P. and Min-Allah N. and Matsui K. and Ossowski S. and Rodríguez S.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85218979175&doi=10.1007%2f978-3-031-82073-1_5&partnerID=40&md5=b136d4a114ce5acfa89f907ccecc145f},
doi = {10.1007/978-3-031-82073-1_5},
isbn = {23673370 (ISSN); 978-303182072-4 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Lect. Notes Networks Syst.},
volume = {1259},
pages = {43–52},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {Mental health issues are becoming more prevalent among university students. The mindful self-compassion (MSC) training program, which was introduced to address this issue, has shown some efficacy. However, many people, particularly Japanese people, have difficulty recalling visual imagery or feel uncomfortable or resistant to treating themselves with compassion. This study proposes and develops a system that uses virtual space and avatars to help individuals improve their self-compassion. In the proposed system, the user first selects an avatar of a person with whom to talk (hereafter referred to as “partner”), and then talks about the problem to the avatar of his/her choice. Next, the user changes viewpoints and listens to the problem as the partner’s avatar and responds with compassion. Finally, the user returns to his/her own avatar and listens to the compassionate response spoken as the partner avatar. We first conducted surveys to understand the important system components, and then developed prototypes. In light of the results of the experiments, we improved the prototype by introducing a generative AI. The first prototype used the user’s spoken voice as it was, but the improved system uses the generative AI to organize and convert the voice and present it. In addition, we added a function to generate and add advice with compression. The proposed system is expected to contribute to the improvement of students’ self-compassion. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},
keywords = {Avatar, Generative adversarial networks, Generative AI, Health issues, Mental health, Self-compassion, Students, Training program, University students, Virtual avatar, Virtual environments, Virtual Reality, Virtual Space, Virtual spaces, Visual imagery},
pubstate = {published},
tppubtype = {inproceedings}
}
2024
Scott, A. J. S.; McCuaig, F.; Lim, V.; Watkins, W.; Wang, J.; Strachan, G.
Revolutionizing Nurse Practitioner Training: Integrating Virtual Reality and Large Language Models for Enhanced Clinical Education Proceedings Article
In: G., Strudwick; N.R., Hardiker; G., Rees; R., Cook; R., Cook; Y.J., Lee (Ed.): Stud. Health Technol. Informatics, pp. 671–672, IOS Press BV, 2024, ISBN: 09269630 (ISSN); 978-164368527-4 (ISBN).
Abstract | Links | BibTeX | Tags: 3D modeling, 3D models, 3d-modeling, adult, anamnesis, clinical decision making, clinical education, Clinical Simulation, Computational Linguistics, computer interface, Computer-Assisted Instruction, conference paper, Curriculum, Decision making, E-Learning, Education, Health care education, Healthcare Education, human, Humans, Language Model, Large language model, large language models, Mesh generation, Model animations, Modeling languages, nurse practitioner, Nurse Practitioners, Nursing, nursing education, nursing student, OSCE preparation, procedures, simulation, Teaching, therapy, Training, Training program, User-Computer Interface, Virtual Reality, Virtual reality training
@inproceedings{scott_revolutionizing_2024,
title = {Revolutionizing Nurse Practitioner Training: Integrating Virtual Reality and Large Language Models for Enhanced Clinical Education},
author = {A. J. S. Scott and F. McCuaig and V. Lim and W. Watkins and J. Wang and G. Strachan},
editor = {Strudwick G. and Hardiker N.R. and Rees G. and Cook R. and Cook R. and Lee Y.J.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199593781&doi=10.3233%2fSHTI240272&partnerID=40&md5=90c7bd43ba978f942723e6cf1983ffb3},
doi = {10.3233/SHTI240272},
isbn = {09269630 (ISSN); 978-164368527-4 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Stud. Health Technol. Informatics},
volume = {315},
pages = {671–672},
publisher = {IOS Press BV},
abstract = {This project introduces an innovative virtual reality (VR) training program for student Nurse Practitioners, incorporating advanced 3D modeling, animation, and Large Language Models (LLMs). Designed to simulate realistic patient interactions, the program aims to improve communication, history taking, and clinical decision-making skills in a controlled, authentic setting. This abstract outlines the methods, results, and potential impact of this cutting-edge educational tool on nursing education. © 2024 The Authors.},
keywords = {3D modeling, 3D models, 3d-modeling, adult, anamnesis, clinical decision making, clinical education, Clinical Simulation, Computational Linguistics, computer interface, Computer-Assisted Instruction, conference paper, Curriculum, Decision making, E-Learning, Education, Health care education, Healthcare Education, human, Humans, Language Model, Large language model, large language models, Mesh generation, Model animations, Modeling languages, nurse practitioner, Nurse Practitioners, Nursing, nursing education, nursing student, OSCE preparation, procedures, simulation, Teaching, therapy, Training, Training program, User-Computer Interface, Virtual Reality, Virtual reality training},
pubstate = {published},
tppubtype = {inproceedings}
}