Metaverse in Healthcare Integrated with Explainable AI and Blockchain: Enabling Immersiveness, Ensuring Trust, and Providing Patient Data Security

Surveying the Digital Cytology Workflow in Italy: An Initial Report on AI Integration Across Key Professional Roles

BACKGROUND

The integration of artificial intelligence (AI) in healthcare, particularly in digital cytology, has the potential to enhance diagnostic accuracy and workflow efficiency. However, AI adoption remains limited due to technological and human-related barriers. Understanding the perceptions and experiences of healthcare professionals is essential for overcoming these challenges and facilitating effective AI implementation.

OBJECTIVES

This study aimed to assess AI integration in digital cytology workflows by evaluating professionals' perspectives on its benefits, challenges, and requirements for successful adoption.

METHODS

A survey was conducted among 150 professionals working in public and private healthcare settings in Italy, including laboratory technicians (35%), medical doctors (25%), biologists (20%), and specialists in diagnostic technical sciences (20%). Data were collected through a structured Computer-Assisted Web Interview (CAWI) and a Virtual Focus Group (VFG) to capture quantitative and qualitative insights on AI familiarity, perceived advantages, and barriers to adoption.

RESULTS

The findings indicated varying levels of AI familiarity among professionals. While many recognized AI's potential to improve diagnostic accuracy and streamline workflows, concerns were raised regarding resistance to change, implementation costs, and doubts about AI reliability. Participants emphasized the need for structured training and continuous support to facilitate AI adoption in digital cytology.

CONCLUSIONS

Addressing barriers such as resistance, cost, and trust is essential for the successful integration of AI in digital cytology workflows. Tailored training programs and ongoing professional support can enhance AI adoption, ultimately optimizing diagnostic processes and improving clinical outcomes.

MetaRehabVerse: The Great Opportunity to Put the Person's Functioning and Participation at the Center of Healthcare

BACKGROUND AND OBJECTIVE

The metaverse refers to a digital realm accessible via internet connections using virtual reality and augmented reality glasses for promoting a new era of social rehabilitation. It represents the next-generation mobile computing platform expected to see widespread utilization in the future. In the context of rehabilitation, the metaverse is envisioned as a novel approach to enhance the treatment of human functioning exploiting the "synchronized brains" potential exacerbated by social interactions in virtual scenarios.

RESULTS

The metaverse emerges as an ideal domain for adapting the principles of the-International Classification of Functioning. Its intrinsic capacity to simulate interactions within virtual environments shared by multi-users, while providing a profound sense of presence and comprehensive perception, should facilitate learning and experiential understanding. Technical and conceptual aspects are currently under definition, including the interplay with artificial intelligence, definition of social metrics performance, and the utilization of blockchain technology for economic purposes.

CONCLUSION

Building upon these foundations, this paper explores potential areas of metaverse applications in rehabilitation and examines how they may facilitate the pillars outlined in the World Health Organization's Rehabilitation 2030 call for action.

Metaverse for mental health disorders: Opportunities and challenges

Several articles on the mental health impact of the metaverse and the need to balance its potential benefits with the risks of metaverse use has recently published. The metaverse consists of a combination of immersive technologies and artificial intelligence algorithms. The metaverse differs from the preceding digital psychiatric interventions due to its complex structure and interactions between components. The diverse functions of the metaverse ensure that it may have a substantial impact on mental health. However, the evidence for its efficacy in treating mental health disorders is limited to a few trials. The mental health benefits of immersive technologies are well-documented and suggest that metaverse-based psychiatric treatment may be similarly efficacious. The mental health risks of the metaverse are largely unknown, and it is not clear whether they will be greater than other digital psychiatric interventions. Much more research is needed to determine whether metaverse-based psychiatric treatment will meet the standards of appropriate mental healthcare.

Metaverse Clinic for Pregnant Women With Subclinical Hypothyroidism: Prospective Randomized Study

BACKGROUND

Health care is experiencing new opportunities in the emerging digital landscape. The metaverse, a shared virtual space, integrates technologies such as augmented reality, virtual reality, blockchain, and artificial intelligence. It allows users to interact with immersive digital worlds, connect with others, and explore unknowns. While the metaverse is gaining traction across various medical disciplines, its application in thyroid diseases remains unexplored. Subclinical hypothyroidism (SCH) is the most common thyroid disorder during pregnancy and is frequently associated with adverse pregnancy outcomes.

OBJECTIVE

This study aims to evaluate the safety and effectiveness of a metaverse platform in managing SCH during pregnancy.

METHODS

A randomized controlled trial was conducted at Fujian Provincial Hospital, China, from July 2022 to December 2023. A total of 60 pregnant women diagnosed with SCH were randomly assigned into two groups: the standard group (n=30) and the metaverse group (n=30). Both groups received levothyroxine sodium tablets. Additionally, participants in the metaverse group had access to the metaverse virtual medical consultations and metaverse-based medical games. The primary outcomes were adverse maternal and offspring outcomes, and the secondary outcomes included the neurobehavioral development of offspring and maternal psychological assessments.

RESULTS

Of the 30 participants in each group, adverse maternal outcomes were observed in 43% (n=13) of the standard group and 37% (n=11) of the metaverse group (P=.60). The incidence of adverse offspring outcomes was 33% (n=10) in the standard group, compared to 7% (n=2) in the metaverse group (P=.01). The Gesell Development Scale did not show significant differences between the two groups. Notably, the metaverse group demonstrated significantly improved scores on the Self-Rating Depression Scale and the Self-Rating Anxiety Scale scores compared to the standard group (P<.001 and P=.001, respectively).

CONCLUSIONS

The use of metaverse technology significantly reduced the incidence of adverse offspring outcomes and positively impacted maternal mental health. Maternal adverse outcomes and offspring neurobehavioral development were comparable between the two groups.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR2300076803; https://www.chictr.org.cn/showproj.html?proj=205905.

Adversarial Examples on XAI-Enabled DT for Smart Healthcare Systems

There have recently been rapid developments in smart healthcare systems, such as precision diagnosis, smart diet management, and drug discovery. These systems require the integration of the Internet of Things (IoT) for data acquisition, Digital Twins (DT) for data representation into a digital replica and Artificial Intelligence (AI) for decision-making. DT is a digital copy or replica of physical entities (e.g., patients), one of the emerging technologies that enable the advancement of smart healthcare systems. AI and Machine Learning (ML) offer great benefits to DT-based smart healthcare systems. They also pose certain risks, including security risks, and bring up issues of fairness, trustworthiness, explainability, and interpretability. One of the challenges that still make the full adaptation of AI/ML in healthcare questionable is the explainability of AI (XAI) and interpretability of ML (IML). Although the study of the explainability and interpretability of AI/ML is now a trend, there is a lack of research on the security of XAI-enabled DT for smart healthcare systems. Existing studies limit their focus to either the security of XAI or DT. This paper provides a brief overview of the research on the security of XAI-enabled DT for smart healthcare systems. It also explores potential adversarial attacks against XAI-enabled DT for smart healthcare systems. Additionally, it proposes a framework for designing XAI-enabled DT for smart healthcare systems that are secure and trusted.

Utilizing Blockchain Technology for Healthcare and Biomedical Research: A Review

Blockchain is a decentralized, secure, and immutable public ledger that offers significant benefits over conventional centralized systems by preventing data breaches and cyber-attacks. It has a great potential to improve data security, privacy, and interoperability in healthcare and biomedical research. This review discusses the basic principles and the historical evolution of blockchain and evaluates the implications of blockchain for the existing healthcare infrastructure. It also highlights blockchain technology's advantages in electronic health records, supply chain management, clinical trials, and telemedicine. However, this technology faces several hurdles, including regulatory issues, technical complexity, and economic costs, which suggest a gradual adoption over time. In addition, the review emphasizes its ability to ensure data integrity, enhance collaboration, and protect intellectual property in biomedical research. This review shows that blockchain can enhance healthcare data management by providing secure, efficient, and patient-centric solutions. Furthermore, it also discusses the implications of blockchain for the future of healthcare and biomedical research and suggests that ongoing research and interdisciplinary approaches are essential for overcoming current barriers and realizing the full potential of this technology. Future research should focus on developing privacy-preserving hybrid data storage solutions that comply with international laws and regulations, thus enhancing the sustainability and scalability of this technology in healthcare.

Metaverse in surgery - origins and future potential

The metaverse refers to a collective virtual space that combines physical and digital realities to create immersive, interactive environments. This space is powered by technologies such as augmented reality (AR), virtual reality (VR), artificial intelligence (AI) and blockchain. In healthcare, the metaverse can offer many applications. Specifically in surgery, potential uses of the metaverse include the possibility of conducting immersive surgical training in a VR or AR setting, and enhancing surgical planning through the adoption of three-dimensional virtual models and simulated procedures. At the intraoperative level, AR-guided surgery can assist the surgeon in real time to increase surgical precision in tumour identification and selective management of vessels. In post-operative care, potential uses of the metaverse include recovery monitoring and patient education. In urology, AR and VR have been widely explored in the past decade, mainly for surgical navigation in prostate and kidney cancer surgery, whereas only anecdotal metaverse experiences have been reported to date, specifically in partial nephrectomy. In the future, further integration of AI will improve the metaverse experience, potentially increasing the possibility of carrying out surgical navigation, data collection and virtual trials within the metaverse. However, challenges concerning data security and regulatory compliance must be addressed before the metaverse can be used to improve patient care.

Metaverse and its impact on medical education and health care system: A narrative review

Background and Aims

The metaverse has enormous potential in health care, continuously developing and offering innovative solutions by combining artificial intelligence (AI), augmented reality (AR)/virtual reality (VR), Internet of Medical Devices, and quantum computing technologies. In addition to using virtual platforms to help and boost medical education, familiarity with this platform is necessary to strengthen medical skills and communication with patients in medical sciences in the future.

Methods

We conducted a comprehensive search using keywords and their MeSH synonyms, including "metaverse," "medical education," and "health care," across PubMed, Scopus, and Web of Science. After screening the results, relevant articles were selected to inform the writing of this manuscript.

Results

The metaverse is shaping the future of medical sciences, offering new opportunities for health education, advocacy training, and patient outcome improvement. The combination of real and virtual worlds may advance international relations, facilitate data sharing, increase medical care speed, and reduce infectious diseases. The metaverse, despite its benefits, has some limitations. Only 37% of 15-24-year-olds have internet access, and AR/VR glasses are expensive and may cause eye discomfort. It is also a potential risk for medical students, who may need help understanding the limitations of simulations and develop unrealistic expectations. Considering the metaverse as a supplement to clinical practice, not a replacement for supervised training, is crucial. Ethical concerns, data security, privacy, and lack of instructions for education are also issues. However, providing information about the metaverse can increase health care workers' attribution to use it for patient examinations, students' education, and tests.

Conclusion

This paper explores the impact of the metaverse on medical science education and underscores the need to integrate the metaverse into all areas of medical sciences as a supplement to existing evidence.

MetaHealth: unlocking metaverse technologies in digital healthcare

INTRODUCTION

The metaverse is a new digital world powered by cutting-edge technologies that offers tremendous potential for healthcare. The metaverse is anticipated to experience enormous growth and adoption with a rising need for digital healthcare over the next decade. This article offers a comprehensive analysis of the integration of metaverse technologies into healthcare.

AREAS COVERED

This article delves into the multifaceted realm of metaverse technologies within healthcare, offering insights into its diverse contexts. Central to its exploration are the significant contributions, such as examining the current landscape of metaverse technologies in healthcare, offering a nuanced understanding of their applications. The article meticulously explores the array of tools and platforms available for surgical procedures, highlighting their efficacy and it also delves into how these technologies illuminate the evolving landscape of healthcare delivery. Through thorough analysis, this article elucidates the transformative potential of metaverse technologies in revolutionizing healthcare practices.

EXPERT OPINION

The integration of metaverse technologies in healthcare signifies a transformative shift in service delivery. The metaverse, driven by advanced technology, promises substantial changes, enhances medical education, patient care, and research through immersive experiences. This article aims to explore its various contexts heralding a new era in healthcare.

Performance of ChatGPT-4 and Bard chatbots in responding to common patient questions on prostate cancer 177Lu-PSMA-617 therapy

Background

Many patients use artificial intelligence (AI) chatbots as a rapid source of health information. This raises important questions about the reliability and effectiveness of AI chatbots in delivering accurate and understandable information.

Purpose

To evaluate and compare the accuracy, conciseness, and readability of responses from OpenAI ChatGPT-4 and Google Bard to patient inquiries concerning the novel 177Lu-PSMA-617 therapy for prostate cancer.

Materials and methods

Two experts listed the 12 most commonly asked questions by patients on 177Lu-PSMA-617 therapy. These twelve questions were prompted to OpenAI ChatGPT-4 and Google Bard. AI-generated responses were distributed using an online survey platform (Qualtrics) and blindly rated by eight experts. The performances of the AI chatbots were evaluated and compared across three domains: accuracy, conciseness, and readability. Additionally, potential safety concerns associated with AI-generated answers were also examined. The Mann-Whitney U and chi-square tests were utilized to compare the performances of AI chatbots.

Results

Eight experts participated in the survey, evaluating 12 AI-generated responses across the three domains of accuracy, conciseness, and readability, resulting in 96 assessments (12 responses x 8 experts) for each domain per chatbot. ChatGPT-4 provided more accurate answers than Bard (2.95 ± 0.671 vs 2.73 ± 0.732, p=0.027). Bard's responses had better readability than ChatGPT-4 (2.79 ± 0.408 vs 2.94 ± 0.243, p=0.003). Both ChatGPT-4 and Bard achieved comparable conciseness scores (3.14 ± 0.659 vs 3.11 ± 0.679, p=0.798). Experts categorized the AI-generated responses as incorrect or partially correct at a rate of 16.6% for ChatGPT-4 and 29.1% for Bard. Bard's answers contained significantly more misleading information than those of ChatGPT-4 (p = 0.039).

Conclusion

AI chatbots have gained significant attention, and their performance is continuously improving. Nonetheless, these technologies still need further improvements to be considered reliable and credible sources for patients seeking medical information on 177Lu-PSMA-617 therapy.

The Transformative Power of Virtual Hospitals for Revolutionising Healthcare Delivery

Objectives: The objective of this narrative review is to explore the advantages and limitations of VHs in delivering healthcare, including access to specialized professionals, streamlined communication, efficient scheduling, integration of electronic health records, ongoing monitoring, and support, transcending geographical boundaries, and resource optimization. Methods: Review of literature. Results: The national healthcare systems are facing an alarming rise in pressure due to global shifts. Virtual hospitals (VH) offer a practical solution to numerous systemic challenges, including rising costs and increased workloads for healthcare providers. VH also facilitate the delivery of personalized services and enable the monitoring of patients beyond the conventional confines of healthcare settings, reducing the reliance on waiting medicine carried out in doctors' offices or hospitals. Conclusion: VH can mirror the conventional healthcare referral system.

Metaverse in Mental Health: The Beginning of a Long History

PURPOSE OF REVIEW

We review the first pilot studies applying metaverse-related technologies in psychiatric patients and discuss the rationale for using this complex federation of technologies to treat mental diseases. Concerning previous virtual-reality applications in medical care, metaverse technologies provide the unique opportunity to define, control, and shape virtual scenarios shared by multi-users to exploit the "synchronized brains" potential exacerbated by social interactions.

RECENT FINDINGS

The application of an avatar-based sexual therapy program conducted on a metaverse platform has been demonstrated to be more effective concerning traditional sexual coaching for treating female orgasm disorders. Again, a metaverse-based social skills training program has been tested on children with autism spectrum disorders, demonstrating a significant impact on social interaction abilities. Metaverse-related technologies could enable us to develop new reliable approaches for treating diseases where behavioral symptoms can be addressed using socio-attentive tasks and social-interaction strategies.

Unveiling the Metaverse: A survey of user perceptions and the impact of usability, social influence and interoperability

This review explores the Metaverse, focusing on user perceptions and emphasizing the critical aspects of usability, social influence, and interoperability within this emerging digital ecosystem. By integrating various academic perspectives, this analysis highlights the Metaverse's significant impact across various sectors, emphasizing its potential to reshape digital interaction paradigms. The investigation reveals usability as a cornerstone for user engagement, demonstrating how social dynamics profoundly influence user behaviors and choices within virtual environments. Furthermore, the study outlines interoperability as a paramount challenge, advocating for establishing unified protocols and technologies to facilitate seamless experiences across disparate Metaverse platforms. It advocates for the adoption of inclusive, ergonomically oriented designs aimed at enhancing user participation. It addresses the ethical and societal challenges posed by the Metaverse, including concerns related to digital harassment, invasive marketing practices, and breaches of privacy. Additionally, the review identifies existing gaps in the literature, particularly regarding the Metaverse's implications for healthcare, its impact on educational outcomes, and the urgent need for empirical data concerning its long-term effects on user psychology and behavior. By providing a comprehensive synthesis of the current understanding of user experiences and challenges within the Metaverse, this paper contributes to the academic dialogue, laying the groundwork for future research initiatives. It aims to steer the development of the Metaverse towards a trajectory that is ethically sound, socially responsible, inclusive, and aligned with societal expectations, thereby fostering a digital realm that upholds the highest standards of integrity and inclusivity.

Artificial Intelligence in Pediatric Emergency Medicine: Applications, Challenges, and Future Perspectives

The dawn of Artificial intelligence (AI) in healthcare stands as a milestone in medical innovation. Different medical fields are heavily involved, and pediatric emergency medicine is no exception. We conducted a narrative review structured in two parts. The first part explores the theoretical principles of AI, providing all the necessary background to feel confident with these new state-of-the-art tools. The second part presents an informative analysis of AI models in pediatric emergencies. We examined PubMed and Cochrane Library from inception up to April 2024. Key applications include triage optimization, predictive models for traumatic brain injury assessment, and computerized sepsis prediction systems. In each of these domains, AI models outperformed standard methods. The main barriers to a widespread adoption include technological challenges, but also ethical issues, age-related differences in data interpretation, and the paucity of comprehensive datasets in the pediatric context. Future feasible research directions should address the validation of models through prospective datasets with more numerous sample sizes of patients. Furthermore, our analysis shows that it is essential to tailor AI algorithms to specific medical needs. This requires a close partnership between clinicians and developers. Building a shared knowledge platform is therefore a key step.

Factors affecting the adoption of metaverse in healthcare: The moderating role of digital division, and meta-culture

This research aims to find out the factors affecting the adoption of Metaverse in healthcare. This study explores the effect of perceived ease of use, perceived usefulness, and trust on adopting Metaverse in healthcare by keeping digital division and metaculture as moderating variables. The philosophical foundation is rooted in the positivism paradigm, the methodology is quantitative, and the approach used is deductive. Data was collected in Pakistan and China through judgmental sampling from 384 respondents. Partial Least Square Structural Equation Modelling (PLS-SEM) was used to analyze the collected data. The findings validate the relationship between perceived ease of use and the adoption of metaverse with β-value 0.236, t-value 5.207 and p-value 0.000, the relationship between perceived usefulness and the adoption of metaverse with β-value 0.233, t-value 4.017 and p-value 0.000, and the relationship between trust and adoption of a metaverse with β-value 0.192, t-value 3.589 and p-value 0.000. Results also show that the digital divide moderates the relation between perceived ease of use and adopting the metaverse having β-value 0.078, t-value 1.848 and p-value 0.032. Similarly, the findings also show that the digital divide does not moderate the relationships of perceived usefulness and trust with adopting the metaverse. Moreover, the meta culture also does not moderate the relationships of perceived ease of use, usefulness, and trust with adopting the metaverse. The study contributes to theoretical research on adopting a metaverse in healthcare by examining various factors necessary for its development. It also provides guidelines for the developers and adopters of suitable metaverse technology.

[Extended Reality (XR) - Applications in Thoracic Surgery]

Extended reality (XR) includes the sub-terms of virtual reality (VR), augmented reality (AR) and mixed reality (MR) and describes interactive and immersive technologies that replace the real world with digital elements or seamlessly extend it with such approaches. XR thus offers a very wide range of possible applications in medicine. In surgery, and thoracic surgery in particular, XR technologies can be harnessed for treatment planning, navigation, training, and patient information. Such applications are increasingly being tested and need to be evaluated. We provide an overview of the status quo of technical development, current surgical applications of XR, and look into the future of the medical XR landscape with integration of artificial intelligence (AI).

Exploring the Darkverse: A Multi-Perspective Analysis of the Negative Societal Impacts of the Metaverse

The Metaverse has the potential to form the next pervasive computing archetype that can transform many aspects of work and life at a societal level. Despite the many forecasted benefits from the metaverse, its negative outcomes have remained relatively unexplored with the majority of views grounded on logical thoughts derived from prior data points linked with similar technologies, somewhat lacking academic and expert perspective. This study responds to the dark side perspectives through informed and multifaceted narratives provided by invited leading academics and experts from diverse disciplinary backgrounds. The metaverse dark side perspectives covered include: technological and consumer vulnerability, privacy, and diminished reality, human-computer interface, identity theft, invasive advertising, misinformation, propaganda, phishing, financial crimes, terrorist activities, abuse, pornography, social inclusion, mental health, sexual harassment and metaverse-triggered unintended consequences. The paper concludes with a synthesis of common themes, formulating propositions, and presenting implications for practice and policy.

Mental health services in the metaverse: potential and concerns

No abstract available.

Improved Discriminative Object Localization Algorithm for Safety Management of Indoor Construction

Object localization is a sub-field of computer vision-based object recognition technology that identifies object classes and locations. Studies on safety management are still in their infancy, particularly those aimed at lowering occupational fatalities and accidents at indoor construction sites. In comparison to manual procedures, this study suggests an improved discriminative object localization (IDOL) algorithm to aid safety managers with visualization to improve indoor construction site safety management. The IDOL algorithm employs Grad-CAM visualization images from the EfficientNet-B7 classification network to automatically identify internal characteristics pertinent to the set of classes evaluated by the network model without the need for further annotation. To evaluate the performance of the presented algorithm in the study, localization accuracy in 2D coordinates and localization error in 3D coordinates of the IDOL algorithm and YOLOv5 object detection model, a leading object detection method in the current research area, are compared. The comparison findings demonstrate that the IDOL algorithm provides a higher localization accuracy with more precise coordinates than the YOLOv5 model over both 2D images and 3D point cloud coordinates. The results of the study indicate that the IDOL algorithm achieved improved localization performance over the existing YOLOv5 object detection model and, thus, is able to assist with visualization of indoor construction sites in order to enhance safety management.