The Digital Metaverse: Applications in Artificial Intelligence, Medical Education, and Integrative Health

From static web to metaverse: reinventing medical education in the post-pandemic era

The World Wide Web and the advancement of computer technology in the 1960s and 1990s respectively set the ground for a substantial and simultaneous change in many facets of our life, including medicine, health care, and medical education. The traditional didactic approach has shifted towards more dynamic and interactive methods, leveraging technologies such as simulation tools, virtual reality, and online platforms. At the forefront is the remarkable evolution that has revolutionized how medical knowledge is accessed, disseminated, and integrated into pedagogical practices. The COVID-19 pandemic also led to rapid and large-scale adoption of e-learning and digital resources in medical education because of widespread lockdowns, social distancing measures, and the closure of medical schools and healthcare training programs. This review paper examines the evolution of medical education from the Flexnerian era to the modern digital age, closely examining the influence of the evolving WWW and its shift from Education 1.0 to Education 4.0. This evolution has been further accentuated by the transition from the static landscapes of Web 2D to the immersive realms of Web 3D, especially considering the growing notion of the metaverse. The application of the metaverse is an interconnected, virtual shared space that includes virtual reality (VR), augmented reality (AR), and mixed reality (MR) to create a fertile ground for simulation-based training, collaborative learning, and experiential skill acquisition for competency development. This review includes the multifaceted applications of the metaverse in medical education, outlining both its benefits and challenges. Through insightful case studies and examples, it highlights the innovative potential of the metaverse as a platform for immersive learning experiences. Moreover, the review addresses the role of emerging technologies in shaping the post-pandemic future of medical education, ultimately culminating in a series of recommendations tailored for medical institutions aiming to successfully capitalize on revolutionary changes.

Metaverse-powered basic sciences medical education: bridging the gaps for lower middle-income countries

BACKGROUND

Traditional medical education often lacks contextual experience, hindering students' ability to effectively apply theoretical knowledge in real-world scenarios. The integration of the metaverse into medical education holds great enormous promise for addressing educational disparities, particularly in lower-middle-income countries (LMICs) accompanied by rapid technological advancements. This commentary paper aimed to address the potential of the metaverse in enhancing basic sciences education within the constraints faced by universities in LMICs. We also addressed learning design challenges by proposing fundamental design elements and a suggested conceptual framework for developing metaverse-based teaching methods.The goal is to assist educators and medical practitioners in comprehensivley understanding key factors in immersive teaching and learning.

DISCUSSION

By immersing medical students in virtual scenarios mimicking real medical settings and patient interactions, the metaverse enables practice in clinical decision-making, interpersonal skills, and exposure to complex medical situations in a controlled environment. These simulations can be customized to reflect local healthcare challenges, preparing medical students to tackle specific community needs. Various disciplines, including anatomy, physiology, pharmacy, dentistry, and pathology, have begun leveraging the metaverse to offer immersive learning experiences, foster interdisciplinary collaborations, and facilitate authentic assessments. However, financial constraints pose a significant barrier to widespread adoption, particularly in resource-limited settings like LMICs. Addressing these challenges is crucial to realizing the full potential of metaverse technology in medical education.

CONCLUSION

The metaverse offers a promising solution for enhancing medical education by providing immersive, context-rich learning experiences. This paper proposes a conceptual framework and fundamental design elements to aid faculty educators and medical practitioners in effectively incorporating metaverse technology into their teaching methods, thus improving educational outcomes in LMICs.

Principles of digital professionalism for the metaverse in healthcare

BACKGROUND

Experts are currently investigating the potential applications of the metaverse in healthcare. The metaverse, a groundbreaking concept that arose in the early 21st century through the fusion of virtual reality and augmented reality technologies, holds promise for transforming healthcare delivery. Alongside its implementation, the issue of digital professionalism in healthcare must be addressed. Digital professionalism refers to the knowledge and skills required by healthcare specialists to navigate digital technologies effectively and ethically. This study aims to identify the core principles of digital professionalism for the use of metaverse in healthcare.

METHOD

This study utilized a qualitative design and collected data through semi-structured online interviews with 20 medical information and health informatics specialists from various countries (USA, UK, Sweden, Netherlands, Poland, Romania, Italy, Iran). Data analysis was conducted using the open coding method, wherein concepts (codes) related to the themes of digital professionalism for the metaverse in healthcare were assigned to the data. The analysis was performed using the MAXQDA software (VER BI GmbH, Berlin, Germany).

RESULTS

The study revealed ten fundamental principles of digital professionalism for the metaverse in healthcare: Privacy and Security, Informed Consent, Trust and Integrity, Accessibility and Inclusion, Professional Boundaries, Evidence-Based Practice, Continuous Education and Training, Collaboration and Interoperability, Feedback and Improvement, and Regulatory Compliance.

CONCLUSION

As the metaverse continues to expand and integrate itself into various industries, including healthcare, it becomes vital to establish principles of digital professionalism to ensure ethical and responsible practices. Healthcare professionals can uphold these principles to maintain ethical standards, safeguard patient privacy, and deliver effective care within the metaverse.

Research on Artificial-Intelligence-Assisted Medicine: A Survey on Medical Artificial Intelligence

With the improvement of economic conditions and the increase in living standards, people's attention in regard to health is also continuously increasing. They are beginning to place their hopes on machines, expecting artificial intelligence (AI) to provide a more humanized medical environment and personalized services, thus greatly expanding the supply and bridging the gap between resource supply and demand. With the development of IoT technology, the arrival of the 5G and 6G communication era, and the enhancement of computing capabilities in particular, the development and application of AI-assisted healthcare have been further promoted. Currently, research on and the application of artificial intelligence in the field of medical assistance are continuously deepening and expanding. AI holds immense economic value and has many potential applications in regard to medical institutions, patients, and healthcare professionals. It has the ability to enhance medical efficiency, reduce healthcare costs, improve the quality of healthcare services, and provide a more intelligent and humanized service experience for healthcare professionals and patients. This study elaborates on AI development history and development timelines in the medical field, types of AI technologies in healthcare informatics, the application of AI in the medical field, and opportunities and challenges of AI in the field of medicine. The combination of healthcare and artificial intelligence has a profound impact on human life, improving human health levels and quality of life and changing human lifestyles.

Enhancing learning motivation and academic achievement in nursing students through metaverse-based learning: A randomized controlled study

AIM

Generation Z students do not get much benefit from traditional distance education methods. Instead, they need new platforms and methods that will motivate them and increase their success.

METHODS

A randomized controlled study was performed on 42 students. The experimental group students were presented with metaverse, and the control group students were taught the distance education course.

RESULTS

In this study, in the students' Instructional Materials Motivation Survey, the mean scores of both the experimental and control groups exhibited no significant difference before the intervention. Regarding the effect of metaverse-based learning on students' Instructional Materials Motivation Survey, the mean score of the control group was 82.55 ± 13.18, and the mean score of the experimental group was 96.52 ± 9.54 and there was a significant difference between groups after the intervention. When the academic achievement levels of the groups were examined, it was determined that the experimental group scored 76.57 ± 13.33 and the control group received 64.40 ± 16.42 points. It was determined there was a significant difference between the groups in terms of learning motivation and academic achievement.

CONCLUSION

The study results show that the participants accepted the important role of metaverse as an effective learning method compared to traditional distance education methods. It is recommended to expand the use of metaverse in various fields of nursing education.

The potential of artificial intelligence to revolutionize health care delivery, research, and education in cardiac electrophysiology

The field of electrophysiology (EP) has benefited from numerous seminal innovations and discoveries that have enabled clinicians to deliver therapies and interventions that save lives and promote quality of life. The rapid pace of innovation in EP may be hindered by several challenges including the aging population with increasing morbidity, the availability of multiple costly therapies that, in many instances, confer minor incremental benefit, the limitations of healthcare reimbursement, the lack of response to therapies by some patients, and the complications of the invasive procedures performed. To overcome these challenges and continue on a steadfast path of transformative innovation, the EP community must comprehensively explore how artificial intelligence (AI) can be applied to healthcare delivery, research, and education and consider all opportunities in which AI can catalyze innovation; create workflow, research, and education efficiencies; and improve patient outcomes at a lower cost. In this white paper, we define AI and discuss the potential of AI to revolutionize the EP field. We also address the requirements for implementing, maintaining, and enhancing quality when using AI and consider ethical, operational, and regulatory aspects of AI implementation. This manuscript will be followed by several perspective papers that will expand on some of these topics.

Metaverse, virtual reality and augmented reality in total shoulder arthroplasty: a systematic review

PURPOSE

This systematic review aims to provide an overview of the current knowledge on the role of the metaverse, augmented reality, and virtual reality in reverse shoulder arthroplasty.

METHODS

A systematic review was performed using the PRISMA guidelines. A comprehensive review of the applications of the metaverse, augmented reality, and virtual reality in in-vivo intraoperative navigation, in the training of orthopedic residents, and in the latest innovations proposed in ex-vivo studies was conducted.

RESULTS

A total of 22 articles were included in the review. Data on navigated shoulder arthroplasty was extracted from 14 articles: seven hundred ninety-three patients treated with intraoperative navigated rTSA or aTSA were included. Also, three randomized control trials (RCTs) reported outcomes on a total of fifty-three orthopedics surgical residents and doctors receiving VR-based training for rTSA, which were also included in the review. Three studies reporting the latest VR and AR-based rTSA applications and two proof of concept studies were also included in the review.

CONCLUSIONS

The metaverse, augmented reality, and virtual reality present immense potential for the future of orthopedic surgery. As these technologies advance, it is crucial to conduct additional research, foster development, and seamlessly integrate them into surgical education to fully harness their capabilities and transform the field. This evolution promises enhanced accuracy, expanded training opportunities, and improved surgical planning capabilities.

Artificial Intelligence and Healthcare Simulation: The Shifting Landscape of Medical Education

The impact of artificial intelligence (AI) will be felt not only in the arena of patient care and deliverable therapies but will also be uniquely disruptive in medical education and healthcare simulation (HCS), in particular. As HCS is intertwined with computer technology, it offers opportunities for rapid scalability with AI and, therefore, will be the most practical place to test new AI applications. This will ensure the acquisition of AI literacy for graduates from the country's various healthcare professional schools. Artificial intelligence has proven to be a useful adjunct in developing interprofessional education and team and leadership skills assessments. Outcome-driven medical simulation has been extensively used to train students in image-centric disciplines such as radiology, ultrasound, echocardiography, and pathology. Allowing students and trainees in healthcare to first apply diagnostic decision support systems (DDSS) under simulated conditions leads to improved diagnostic accuracy, enhanced communication with patients, safer triage decisions, and improved outcomes from rapid response teams. However, the issue of bias, hallucinations, and the uncertainty of emergent properties may undermine the faith of healthcare professionals as they see AI systems deployed in the clinical setting and participating in diagnostic judgments. Also, the demands of ensuring AI literacy in our healthcare professional curricula will place burdens on simulation assets and faculty to adapt to a rapidly changing technological landscape. Nevertheless, the introduction of AI will place increased emphasis on virtual reality platforms, thereby improving the availability of self-directed learning and making it available 24/7, along with uniquely personalized evaluations and customized coaching. Yet, caution must be exercised concerning AI, especially as society's earlier, delayed, and muted responses to the inherent dangers of social media raise serious questions about whether the American government and its citizenry can anticipate the security and privacy guardrails that need to be in place to protect our healthcare practitioners, medical students, and patients.

Beyond words: analyzing non-verbal communication techniques in a medical communication skills course via synchronous online platform

Background

Effective doctor-patient relationships hinge on robust communication skills, with non-verbal communication techniques (NVC) often overlooked, particularly in online synchronous interactions. This study delves into the exploration of NVC types during online feedback sessions for communication skill activities in a medical education module.

Methods

A cohort of 100 first-year medical students and 10 lecturers at the Faculty of Medicine, Universiti Kebangsaan Malaysia (UKM), engaged in communication skills activities via Microsoft Teams. Sessions were recorded, and lecturer NVC, encompassing body position, facial expressions, voice intonation, body movements, eye contact, and paralinguistics, were meticulously observed. Following these sessions, students provided reflective writings highlighting their perceptions of the feedback, specifically focusing on observed NVC.

Results

The study identified consistent non-verbal communication patterns during feedback sessions. Lecturers predominantly leaned forward and toward the camera, maintained direct eye contact, and exhibited dynamic voice intonation. They frequently engaged in tactile gestures and paused to formulate thoughts, often accompanied by filler sounds like "um" and "okay." This consistency suggests proficient use of NVC in providing synchronous online feedback. Less observed NVC included body touching and certain paralinguistic cues like long sighs. Initial student apprehension, rooted in feelings of poor performance during activities, transformed positively upon observing the lecturer's facial expressions and cheerful intonation. This transformation fostered an open reception of feedback, motivating students to address communication skill deficiencies. Additionally, students expressed a preference for comfortable learning environments to alleviate uncertainties during feedback reception. Potential contrivances in non-verbal communication (NVC) due to lecturer awareness of being recorded, a small sample size of 10 lecturers limiting generalizability, a focus solely on preclinical lecturers, and the need for future research to address these constraints and explore diverse educational contexts.

Conclusion

Medical schools globally should prioritize integrating NVC training into their curricula to equip students with essential communication skills for diverse healthcare settings. The study's findings serve as a valuable reference for lecturers, emphasizing the importance of employing effective NVC during online feedback sessions. This is crucial as NVC, though occurring online synchronously, remains pivotal in conveying nuanced information. Additionally, educators require ongoing professional development to enhance proficiency in utilizing NVC techniques in virtual learning environments. Potential research directions stemming from the study's findings include longitudinal investigations into the evolution of NVC patterns, comparative analyses across disciplines, cross-cultural examinations, interventions to improve NVC skills, exploration of technology's role in NVC enhancement, qualitative studies on student perceptions, and interdisciplinary collaborations to deepen understanding of NVC in virtual learning environments.

A scoping review of artificial intelligence in medical education: BEME Guide No. 84

BACKGROUND

Artificial Intelligence (AI) is rapidly transforming healthcare, and there is a critical need for a nuanced understanding of how AI is reshaping teaching, learning, and educational practice in medical education. This review aimed to map the literature regarding AI applications in medical education, core areas of findings, potential candidates for formal systematic review and gaps for future research.

METHODS

This rapid scoping review, conducted over 16 weeks, employed Arksey and O'Malley's framework and adhered to STORIES and BEME guidelines. A systematic and comprehensive search across PubMed/MEDLINE, EMBASE, and MedEdPublish was conducted without date or language restrictions. Publications included in the review spanned undergraduate, graduate, and continuing medical education, encompassing both original studies and perspective pieces. Data were charted by multiple author pairs and synthesized into various thematic maps and charts, ensuring a broad and detailed representation of the current landscape.

RESULTS

The review synthesized 278 publications, with a majority (68%) from North American and European regions. The studies covered diverse AI applications in medical education, such as AI for admissions, teaching, assessment, and clinical reasoning. The review highlighted AI's varied roles, from augmenting traditional educational methods to introducing innovative practices, and underscores the urgent need for ethical guidelines in AI's application in medical education.

CONCLUSION

The current literature has been charted. The findings underscore the need for ongoing research to explore uncharted areas and address potential risks associated with AI use in medical education. This work serves as a foundational resource for educators, policymakers, and researchers in navigating AI's evolving role in medical education. A framework to support future high utility reporting is proposed, the FACETS framework.

Advancing nursing practice with artificial intelligence: Enhancing preparedness for the future

AIM

This article aimed to explore the role of AI in advancing nursing practice, focusing on its impact on readiness for the future.

DESIGN AND METHODS

A position paper, the methodology comprises three key steps. First, a comprehensive literature search using specific keywords in reputable databases was conducted to gather current information on AI in nursing. Second, data extraction and synthesis from selected articles were performed. Finally, a thematic analysis identifies recurring themes to provide insights into AI's impact on future nursing practice.

RESULTS

The findings highlight the transformative role of AI in advancing nursing practice and preparing nurses for the future, including enhancing nursing practice with AI, preparing nurses for the future (AI education and training) and associated, ethical considerations and challenges. AI-enabled robotics and telehealth solutions expand the reach of nursing care, improving accessibility of healthcare services and remote monitoring capabilities of patients' health conditions.

Reimagining Core Entrustable Professional Activities for Undergraduate Medical Education in the Era of Artificial Intelligence

The proliferation of generative artificial intelligence (AI) and its extensive potential for integration into many aspects of health care signal a transformational shift within the health care environment. In this context, medical education must evolve to ensure that medical trainees are adequately prepared to navigate the rapidly changing health care landscape. Medical education has moved toward a competency-based education paradigm, leading the Association of American Medical Colleges (AAMC) to define a set of Entrustable Professional Activities (EPAs) as its practical operational framework in undergraduate medical education. The AAMC's 13 core EPAs for entering residencies have been implemented with varying levels of success across medical schools. In this paper, we critically assess the existing core EPAs in the context of rapid AI integration in medicine. We identify EPAs that require refinement, redefinition, or comprehensive change to align with the emerging trends in health care. Moreover, this perspective proposes a set of "emerging" EPAs, informed by the changing landscape and capabilities presented by generative AI technologies. We provide a practical evaluation of the EPAs, alongside actionable recommendations on how medical education, viewed through the lens of the AAMC EPAs, can adapt and remain relevant amid rapid technological advancements. By leveraging the transformative potential of AI, we can reshape medical education to align with an AI-integrated future of medicine. This approach will help equip future health care professionals with technological competence and adaptive skills to meet the dynamic and evolving demands in health care.

Artificial Intelligence-Based Hazard Detection in Robotic-Assisted Single-Incision Oncologic Surgery

THE PROBLEM

Single-incision surgery is a complex procedure in which any additional information automatically collected from the operating field can be of significance. While the use of robotic devices has greatly improved surgical outcomes, there are still many unresolved issues. One of the major surgical complications, with higher occurrence in cancer patients, is intraoperative hemorrhages, which if detected early, can be more efficiently controlled.

AIM

This paper proposes a hazard detection system which incorporates the advantages of both Artificial Intelligence (AI) and Augmented Reality (AR) agents, capable of identifying, in real-time, intraoperative bleedings, which are subsequently displayed on a Hololens 2 device.

METHODS

The authors explored the different techniques for real-time processing and determined, based on a critical analysis, that YOLOv5 is one of the most promising solutions. An innovative, real-time, bleeding detection system, developed using the YOLOv5 algorithm and the Hololens 2 device, was evaluated on different surgical procedures and tested in multiple configurations to obtain the optimal prediction time and accuracy.

RESULTS

The detection system was able to identify the bleeding occurrence in multiple surgical procedures with a high rate of accuracy. Once detected, the area of interest was marked with a bounding box and displayed on the Hololens 2 device. During the tests, the system was able to differentiate between bleeding occurrence and intraoperative irrigation; thus, reducing the risk of false-negative and false-positive results.

CONCLUSION

The current level of AI and AR technologies enables the development of real-time hazard detection systems as efficient assistance tools for surgeons, especially in high-risk interventions.

[New perspectives in orthopedics : Developments through neurotechnology and metaverse]

The combination of neurotechnology and metaverse holds high potentials for orthopedics, as it offers a broad spectrum of possibilities to overcome the limits of traditional medical care. The vision of a medical metaverse providing the infrastructure as a link for innovative technologies opens up new opportunities for therapy, medical collaborations and practical, personalized training for aspiring physicians. However, risks and challenges, such as security and privacy, health-related issues, acceptance by patients and doctors, as well as technical hurdles and access to the technologies, remain. Hence, future research and development is paramount. Nonetheless, due to technological progress, the exploration of new research areas, and the improved availability of the technologies paired with cost reduction, the prospects for neurotechnology and metaverse in orthopedics are promising.