AHCI RESEARCH GROUP

Publications

Papers published in international journals,
proceedings of conferences, workshops and books.

OUR RESEARCH

Scientific Publications

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2024

Kapadia, N.; Gokhale, S.; Nepomuceno, A.; Cheng, W.; Bothwell, S.; Mathews, M.; Shallat, J. S.; Schultz, C.; Gupta, A.

Evaluation of Large Language Model Generated Dialogues for an AI Based VR Nurse Training Simulator Proceedings Article

In: J.Y.C., Chen; G., Fragomeni (Ed.): Lect. Notes Comput. Sci., pp. 200–212, Springer Science and Business Media Deutschland GmbH, 2024, ISBN: 03029743 (ISSN); 978-303161040-0 (ISBN).

Abstract | Links | BibTeX | Tags: Bard, ChatGPT, ClaudeAI, Clinical research, Computational Linguistics, Dialogue Generation, Dialogue generations, Education computing, Extended reality, Health care education, Healthcare Education, Language Model, Language processing, Large language model, large language models, Natural Language Processing, Natural language processing systems, Natural languages, Nurse Training Simulation, Nursing, Patient avatar, Patient Avatars, Semantics, Students, Training simulation, Virtual Reality

@inproceedings{kapadia_evaluation_2024,

title = {Evaluation of Large Language Model Generated Dialogues for an AI Based VR Nurse Training Simulator},

author = {N. Kapadia and S. Gokhale and A. Nepomuceno and W. Cheng and S. Bothwell and M. Mathews and J. S. Shallat and C. Schultz and A. Gupta},

editor = {Chen J.Y.C. and Fragomeni G.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196200653&doi=10.1007%2f978-3-031-61041-7_13&partnerID=40&md5=8890a8d0c289fdf6e7ab82e105249097},

doi = {10.1007/978-3-031-61041-7_13},

isbn = {03029743 (ISSN); 978-303161040-0 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Lect. Notes Comput. Sci.},

volume = {14706 LNCS},

pages = {200–212},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {This paper explores the efficacy of Large Language Models (LLMs) in generating dialogues for patient avatars in Virtual Reality (VR) nurse training simulators. With the integration of technology in healthcare education evolving rapidly, the potential of NLP to enhance nurse training through realistic patient interactions presents a significant opportunity. Our study introduces a novel LLM-based dialogue generation system, leveraging models such as ChatGPT, GoogleBard, and ClaudeAI. We detail the development of our script generation system, which was a collaborative endeavor involving nurses, technical artists, and developers. The system, tested on the Meta Quest 2 VR headset, integrates complex dialogues created through a synthesis of clinical expertise and advanced NLP, aimed at simulating real-world nursing scenarios. Through a comprehensive evaluation involving lexical and semantic similarity tests compared to clinical expert-generated scripts, we assess the potential of LLMs as suitable alternatives for script generation. The findings aim to contribute to the development of a more interactive and effective VR nurse training simulator, enhancing communication skills among nursing students for improved patient care outcomes. This research underscores the importance of advanced NLP applications in healthcare education, offering insights into the practicality and limitations of employing LLMs in clinical training environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.},

keywords = {Bard, ChatGPT, ClaudeAI, Clinical research, Computational Linguistics, Dialogue Generation, Dialogue generations, Education computing, Extended reality, Health care education, Healthcare Education, Language Model, Language processing, Large language model, large language models, Natural Language Processing, Natural language processing systems, Natural languages, Nurse Training Simulation, Nursing, Patient avatar, Patient Avatars, Semantics, Students, Training simulation, Virtual Reality},

pubstate = {published},

tppubtype = {inproceedings}

}

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}

}