The next generation of healthcare ecosystem in the metaverse.

The Metaverse has gained wide attention for being the application interface for the next generation of Internet. The potential of the Metaverse is growing, as Web 3·0 development and adoption continues to advance medicine and healthcare. We define the next generation of interoperable healthcare ecosystem in the Metaverse. We examine the existing literature regarding the Metaverse, explain the technology framework to deliver an immersive experience, along with a technical comparison of legacy and novel Metaverse platforms that are publicly released and in active use. The potential applications of different features of the Metaverse, including avatar-based meetings, immersive simulations, and social interactions are examined with different roles from patients to healthcare providers and healthcare organizations. Present challenges in the development of the Metaverse healthcare ecosystem are discussed, along with potential solutions including capabilities requiring technological innovation, use cases requiring regulatory supervision, and sound governance. This proposed concept and framework of the Metaverse could potentially redefine the traditional healthcare system and enhance digital transformation in healthcare. Similar to AI technology at the beginning of this decade, real-world development and implementation of these capabilities are relatively nascent. Further pragmatic research is needed for the development of an interoperable healthcare ecosystem in the Metaverse.

Remote Perimetry in a Virtual Reality Metaverse Environment for Out-of-Hospital Functional Eye Screening Compared Against the Gold Standard Humphrey Visual Fields Perimeter: Proof-of-Concept Pilot Study.

BACKGROUND: The growing global burden of visual impairment necessitates better population eye screening for early detection of eye diseases. However, accessibility to testing is often limited and centralized at in-hospital settings. Furthermore, many eye screening programs were disrupted by the COVID-19 pandemic, presenting an urgent need for out-of-hospital solutions. OBJECTIVE: This study investigates the performance of a novel remote perimetry application designed in a virtual reality metaverse environment to enable functional testing in community-based and primary care settings. METHODS: This was a prospective observational study investigating the performance of a novel remote perimetry solution in comparison with the gold standard Humphrey visual field (HVF) perimeter. Subjects received a comprehensive ophthalmologic assessment, HVF perimetry, and remote perimetry testing. The primary outcome measure was the agreement in the classification of overall perimetry result normality by the HVF (Swedish interactive threshold algorithm-fast) and testing with the novel algorithm. Secondary outcome measures included concordance of individual testing points and perimetry topographic maps. RESULTS: We recruited 10 subjects with an average age of 59.6 (range 28-81) years. Of these, 7 (70%) were male and 3 (30%) were female. The agreement in the classification of overall perimetry results was high (9/10, 90%). The pointwise concordance in the automated classification of individual test points was 83.3% (8.2%; range 75%-100%). In addition, there was good perimetry topographic concordance with the HVF in all subjects. CONCLUSIONS: Remote perimetry in a metaverse environment had good concordance with gold standard perimetry using the HVF and could potentially avail functional eye screening in out-of-hospital settings.

Development and testing of a multi-lingual Natural Language Processing-based deep learning system in 10 languages for COVID-19 pandemic crisis: A multi-center study.

Purpose: The COVID-19 pandemic has drastically disrupted global healthcare systems. With the higher demand for healthcare and misinformation related to COVID-19, there is a need to explore alternative models to improve communication. Artificial Intelligence (AI) and Natural Language Processing (NLP) have emerged as promising solutions to improve healthcare delivery. Chatbots could fill a pivotal role in the dissemination and easy accessibility of accurate information in a pandemic. In this study, we developed a multi-lingual NLP-based AI chatbot, DR-COVID, which responds accurately to open-ended, COVID-19 related questions. This was used to facilitate pandemic education and healthcare delivery. Methods: First, we developed DR-COVID with an ensemble NLP model on the Telegram platform (https://t.me/drcovid_nlp_chatbot). Second, we evaluated various performance metrics. Third, we evaluated multi-lingual text-to-text translation to Chinese, Malay, Tamil, Filipino, Thai, Japanese, French, Spanish, and Portuguese. We utilized 2,728 training questions and 821 test questions in English. Primary outcome measurements were (A) overall and top 3 accuracies; (B) Area Under the Curve (AUC), precision, recall, and F1 score. Overall accuracy referred to a correct response for the top answer, whereas top 3 accuracy referred to an appropriate response for any one answer amongst the top 3 answers. AUC and its relevant matrices were obtained from the Receiver Operation Characteristics (ROC) curve. Secondary outcomes were (A) multi-lingual accuracy; (B) comparison to enterprise-grade chatbot systems. The sharing of training and testing datasets on an open-source platform will also contribute to existing data. Results: Our NLP model, utilizing the ensemble architecture, achieved overall and top 3 accuracies of 0.838 [95% confidence interval (CI): 0.826-0.851] and 0.922 [95% CI: 0.913-0.932] respectively. For overall and top 3 results, AUC scores of 0.917 [95% CI: 0.911-0.925] and 0.960 [95% CI: 0.955-0.964] were achieved respectively. We achieved multi-linguicism with nine non-English languages, with Portuguese performing the best overall at 0.900. Lastly, DR-COVID generated answers more accurately and quickly than other chatbots, within 1.12-2.15 s across three devices tested. Conclusion: DR-COVID is a clinically effective NLP-based conversational AI chatbot, and a promising solution for healthcare delivery in the pandemic era.

Metaverse and Virtual Health Care in Ophthalmology: Opportunities and Challenges.

ABSTRACT: The outbreak of the coronavirus disease 2019 has further increased the urgent need for digital transformation within the health care settings, with the use of artificial intelligence/deep learning, internet of things, telecommunication network/virtual platform, and blockchain. The recent advent of metaverse, an interconnected online universe, with the synergistic combination of augmented, virtual, and mixed reality described several years ago, presents a new era of immersive and real-time experiences to enhance human-to-human social interaction and connection. In health care and ophthalmology, the creation of virtual environment with three-dimensional (3D) space and avatar, could be particularly useful in patient-fronting platforms (eg, telemedicine platforms), operational uses (eg, meeting organization), digital education (eg, simulated medical and surgical education), diagnostics, and therapeutics. On the other hand, the implementation and adoption of these emerging virtual health care technologies will require multipronged approaches to ensure interoperability with real-world virtual clinical settings, user-friendliness of the technologies and clinical efficiencies while complying to the clinical, health economics, regulatory, and cybersecurity standards. To serve the urgent need, it is important for the eye community to continue to innovate, invent, adapt, and harness the unique abilities of virtual health care technology to provide better eye care worldwide.

The Impact and Applications of Social Media Platforms for Public Health Responses Before and During the COVID-19 Pandemic: Systematic Literature Review.

BACKGROUND: Social media platforms have numerous potential benefits and drawbacks on public health, which have been described in the literature. The COVID-19 pandemic has exposed our limited knowledge regarding the potential health impact of these platforms, which have been detrimental to public health responses in many regions. OBJECTIVE: This review aims to highlight a brief history of social media in health care and report its potential negative and positive public health impacts, which have been characterized in the literature. METHODS: We searched electronic bibliographic databases including PubMed, including Medline and Institute of Electrical and Electronics Engineers Xplore, from December 10, 2015, to December 10, 2020. We screened the title and abstracts and selected relevant reports for review of full text and reference lists. These were analyzed thematically and consolidated into applications of social media platforms for public health. RESULTS: The positive and negative impact of social media platforms on public health are catalogued on the basis of recent research in this report. These findings are discussed in the context of improving future public health responses and incorporating other emerging digital technology domains such as artificial intelligence. However, there is a need for more research with pragmatic methodology that evaluates the impact of specific digital interventions to inform future health policy. CONCLUSIONS: Recent research has highlighted the potential negative impact of social media platforms on population health, as well as potentially useful applications for public health communication, monitoring, and predictions. More research is needed to objectively investigate measures to mitigate against its negative impact while harnessing effective applications for the benefit of public health.

The Historical Evolution of Ocular Tuberculosis: Past, Present, and Future.

Ocular involvement is a rare manifestation of tuberculosis. Four key issues historically faced by clinicians when diagnosing and treating ocular tuberculosis - diagnostic uncertainty, naturally heterogeneous presentations, limitations of existing laboratory diagnostic tools, and non-uniform treatment guidelines - continue to test today's physicians. Unparalleled scientific and clinical developments over the past century have greatly expanded the knowledge surrounding this challenging ophthalmic condition. Experience with large volumes of cases at tuberculosis-endemic centres has led to recent growth in knowledge and physician experience, perhaps more so in developing countries. Looking forward, the role of diverse new technologies, including artificial intelligence and proteomics, will advance ocular tuberculosis research. Efforts have been made to address the lack of standardized nomenclature, diagnostic uncertainty, and unvalidated, geographically variable treatment guidelines.

The application of clinical registries in ophthalmic trauma-the International Globe and Adnexal Trauma Epidemiology Study (IGATES).

Ophthalmic trauma is a leading cause of preventable monocular blindness worldwide. The prevalence of ophthalmic trauma varies considerably based on geographic location, socio-economic status, age groups, occupation, and cultural practices such as firework celebrations. Clinical registries are known to be valuable in guiding the diagnosis, management, and prognostication of complex diseases. However, there is currently a lack of a centralized international data repository for ophthalmic trauma. We draw lessons from past and existing clinical registries related to ophthalmology and propose a new suitable international multicenter clinical registry for ophthalmic trauma: the International Globe and Adnexal Trauma Epidemiology Study (IGATES). IGATES is hosted on a secure web-based platform which exhibits user-friendly smart features, an integrated Ocular Trauma Score (OTS) prognosis calculator, efficient data collection points, and schematic graphical software. IGATES currently has 37 participating centers globally. The data collected through IGATES will be primarily used to develop a more robust and improved ophthalmic trauma prognostic classification system, the Ocular Trauma Score-2 (OTS-2), which builds on previous systems such as the Birmingham Eye Trauma Terminology System (BETTS) and Ocular Trauma Score (OTS). Furthermore, IGATES will act as a springboard for further research into the epidemiology, diagnosis, and management of ophthalmic trauma. Ultimately, IGATES serves to advance the field of ophthalmic trauma and improve the care that patients with ophthalmic trauma receive.

Considerations for Artificial Intelligence Real-World Implementation in Ophthalmology: Providers' and Patients' Perspectives.

ABSTRACT: Artificial Intelligence (AI), in particular deep learning, has made waves in the health care industry, with several prominent examples shown in ophthalmology. Despite the burgeoning reports on the development of new AI algorithms for detection and management of various eye diseases, few have reached the stage of regulatory approval for real-world implementation. To better enable real-world translation of AI systems, it is important to understand the demands, needs, and concerns of both health care professionals and patients, as providers and recipients of clinical care are impacted by these solutions. This review outlines the advantages and concerns of incorporating AI in ophthalmology care delivery, from both the providers' and patients' perspectives, and the key enablers for seamless transition to real-world implementation.

Epidemiology and outcomes of open globe injuries: the international globe and adnexal trauma epidemiology study (IGATES).

PURPOSE: To detail the methodology for a novel ocular trauma registry and utilize the registry to determine the demographics, nature of injury, and associations of severe visual loss for open globe injuries (OGI). METHODS: Thirteen hospitals in 7 countries used International Globe and Adnexal Trauma Epidemiology Study (IGATES) platform. Patients presenting between April 2009 and 2020 with OGI (with or without) adnexal involvement or intraocular foreign body (IOFB) were included. RESULTS: Analyses of presenting and final VA, using "severe vision loss" (VA ≤ 6/60) and "no severe loss" (VA > 6/60), were performed. Four hundred fifty-four (64%) patients had VA < 6/60 at presentation and 327 (44.8%) at final follow-up, with a highly significant association between presenting and final VA (p < 0.0001). From the cohort of 746 patients, 37 were missing VA at presentation and 16 at follow-up and complete clinical data was available for 354 patients. The male to female ratio is 6:1, and mean age 36.0 ± 20.0 years old. Relative afferent pupillary defect (RAPD), zone III injury, IOFB, and eyelid injury at presentation were recorded in 50 (6.7%), 55 (7.8%), 97 (13%), and 87 (11.7%) patients, respectively, and were significantly associated with VA < 6/60 at follow-up. Older age, ≥ 61 years, was associated with 3.39 times (95% CI: 1.95-5.89) higher risk than ≤20-year-old patients (p < 0.0001) and males 0.424 times (95% CI: 0.27-0.70) lower risk than female (p = 0.0001) of severe vision loss (SVL). CONCLUSION: In OGIs from 13 hospitals, female gender, older age, zone III injury, eyelid injury, and IOFB were associated with higher risk of visual outcome of SVL.

COVID-19 awareness, knowledge and perception towards digital health in an urban multi-ethnic Asian population.

This study aimed to determine COVID-19-related awareness, knowledge, impact and preparedness among elderly Asians; and to evaluate their acceptance towards digital health services amidst the pandemic. 523 participants (177 Malays, 171 Indians, 175 Chinese) were recruited and underwent standardised phone interview during Singapore's lockdown period (07 April till 01 June 2020). Multivariable logistic regression models were performed to evaluate the associations between demographic, socio-economic, lifestyle, and systemic factors, with COVID-19 awareness, knowledge, preparedness, well-being and digital health service acceptance. The average perception score on the seriousness of COVID-19 was 7.6 ± 2.4 (out of 10). 75.5% of participants were aware that COVID-19 carriers can be asymptomatic. Nearly all (≥ 90%) were aware of major prevention methods for COVID-19 (i.e. wearing of mask, social distancing). 66.2% felt prepared for the pandemic, and 86.8% felt confident with government's handling and measures. 78.4% felt their daily routine was impacted. 98.1% reported no prior experience in using digital health services, but 52.2% felt these services would be helpful to reduce non-essential contact. 77.8% were uncomfortable with artificial intelligence software interpreting their medical results. In multivariable analyses, Chinese participants felt less prepared, and more likely felt impacted by COVID-19. Older and lower income participants were less likely to use digital health services. In conclusion, we observed a high level of awareness and knowledge on COVID-19. However, acceptance towards digital health service was low. These findings are valuable for examining the effectiveness of COVID-19 communication in Singapore, and the remaining gaps in digital health adoption among elderly.

Applications of digital health for public health responses to COVID-19: a systematic scoping review of artificial intelligence, telehealth and related technologies.

The coronavirus disease 2019 (COVID-19) pandemic has overwhelmed healthcare services, faced with the twin challenges in acutely meeting the medical needs of patients with COVID-19 while continuing essential services for non-COVID-19 illnesses. The need to re-invent, re-organize and transform healthcare and co-ordinate clinical services at a population level is urgent as countries that controlled initial outbreaks start to experience resurgences. A wide range of digital health solutions have been proposed, although the extent of successful real-world applications of these technologies is unclear. This study aims to review applications of artificial intelligence (AI), telehealth, and other relevant digital health solutions for public health responses in the healthcare operating environment amidst the COVID-19 pandemic. A systematic scoping review was performed to identify potentially relevant reports. Key findings include a large body of evidence for various clinical and operational applications of telehealth (40.1%, n = 99/247). Although a large quantity of reports investigated applications of artificial intelligence (AI) (44.9%, n = 111/247) and big data analytics (36.0%, n = 89/247), weaknesses in study design limit generalizability and translation, highlighting the need for more pragmatic real-world investigations. There were also few descriptions of applications for the internet of things (IoT) (2.0%, n = 5/247), digital platforms for communication (DC) (10.9%, 27/247), digital solutions for data management (DM) (1.6%, n = 4/247), and digital structural screening (DS) (8.9%, n = 22/247); representing gaps and opportunities for digital public health. Finally, the performance of digital health technology for operational applications related to population surveillance and points of entry have not been adequately evaluated.

Telehealth Demand Trends During the COVID-19 Pandemic in the Top 50 Most Affected Countries: Infodemiological Evaluation.

BACKGROUND: The COVID-19 pandemic has led to urgent calls for the adoption of telehealth solutions. However, public interest and demand for telehealth during the pandemic remain unknown. OBJECTIVE: We used an infodemiological approach to estimate the worldwide demand for telehealth services during COVID-19, focusing on the 50 most affected countries and comparing the demand for such services with the level of information and communications technology (ICT) infrastructure available. METHODS: We used Google Trends, the Baidu Index (China), and Yandex Keyword Statistics (Russia) to extract data on worldwide and individual countries' telehealth-related internet searches from January 1 to July 7, 2020, presented as relative search volumes (RSV; range 0-100). Daily COVID-19 cases and deaths were retrieved from the World Health Organization. Individual countries' ICT infrastructure profiles were retrieved from the World Economic Forum Report. RESULTS: Across the 50 countries, the mean RSV was 18.5 (SD 23.2), and the mean ICT index was 62.1 (SD 15.0). An overall spike in worldwide telehealth-related RSVs was observed from March 11, 2020 (RSV peaked to 76.0), which then tailed off in June-July 2020 (mean RSV for the period was 25.8), but remained higher than pre-March RSVs (mean 7.29). By country, 42 (84%) manifested increased RSVs over the evaluation period, with the highest observed in Canada (RSV=100) and the United States (RSV=96). When evaluating associations between RSV and the ICT index, both the United States and Canada demonstrated high RSVs and ICT scores (≥70.3). In contrast, European countries had relatively lower RSVs (range 3.4-19.5) despite high ICT index scores (mean 70.3). Several Latin American (Brazil, Chile, Colombia) and South Asian (India, Bangladesh, Pakistan) countries demonstrated relatively higher RSVs (range 13.8-73.3) but low ICT index scores (mean 44.6), indicating that the telehealth demand outstrips the current ICT infrastructure. CONCLUSIONS: There is generally increased interest and demand for telehealth services across the 50 countries most affected by COVID-19, highlighting the need to scale up telehealth capabilities, during and beyond the pandemic.

The Collaborative Ocular Tuberculosis Study (COTS)-1: A Multinational Review of 447 Patients with Tubercular Intermediate Uveitis and Panuveitis.

Purpose: Tubercular intermediate uveitis (TIU) and panuveitis (TBP) are difficult to manage because of limitations in diagnostic tools and lack of evidence-based treatment guidelines. The Collaborative Ocular Tuberculosis Study (COTS) analyzed treatment regimens and therapeutic outcomes in patients with TIU and TBP.Methods: Multicentre retrospective analysis.Results A total of 138 TIU and 309 TBP patients were included. A total of 382 subjects received antitubercular therapy (ATT) (n = 382/447; 85.4%) and 382 received corticosteroids (n = 382/447; 85.4%). Treatment failure was observed in 78 individuals (n = 78/447; 17.4%), occurring less frequently in patients receiving ATT (n = 66/382; 17.2%) compared to those who did not (n = 12/65; 18.5%). The study did not show any statistically significant therapeutic effect of ATT in patients with TIU and TBP.Conclusion Taking into account the limitations of the retrospective, non-randomized study design, resultant reliance on reported data records, and unequal size of the samples, the current study cannot provide conclusive evidence on the therapeutic benefit of ATT in TIU and TBP.

The Collaborative Ocular Tuberculosis Study (COTS)-1: A Multinational Descriptive Review of Tubercular Uveitis in Paediatric Population.

Purpose: To examine disease profile of tubercular uveitis (TBU) in Paediatric population.Methods: Among 945 patients of the retrospective multinational study by the Collaborative Ocular Tuberculosis Study (COTS)-1, 29 Paediatric patients diagnosed with TBU were analyzed.Results: Mean age of disease presentation was 12.8 (range 4-18 years), with predominance of males (n = 14/20; 70.0%) and Asian ethnicity (n = 25/29; 86.2%). Posterior uveitis (n = 14/28; 50%) was the most frequent uveitis phenotype, with choroidal involvement occurring in 64.7% (n = 11/17). Incidence of optic disc edema and macular edema was higher in children (n = 8/18; 44.4% and n = 5/18; 27.8%, respectively) than in adults (n = 160/942; 16.9% and n = 135/942; 14.3%, respectively). Comparison of optic disc edema between subgroups showed a significant difference (P =.006). All patients received oral corticosteroids, most of them with antitubercular therapy. Treatment failure developed in 4.8% (n = 1/21).Conclusions: Children have a more severe inflammatory response to the disease, and an intensive anti-inflammatory therapeutic regimen is required to achieve a positive treatment outcome.

The Collaborative Ocular Tuberculosis Study (COTS)-1: A Multinational Review of 165 Patients with Tubercular Anterior Uveitis.

Purpose: The Collaborative Ocular Tuberculosis Study (COTS) Group sought to address the diagnostic uncertainty through retrospective cohort analysis of treatment regimens and therapeutic outcomes for patients with tubercular Anterior Uveitis (TAU) across international centers.Methods: Multicentre retrospective analysis of patients diagnosed with TAU between January 2004 to December 2014 that had a minimum follow-up of 1 year.Results: One hundred and sixty-five patients were included. One hundred and seven subjects received antitubercular therapy (ATT) (n = 107/165; 64.9%) with all the patients receiving topical steroid therapy. Treatment failure was noted in 17 patients (n = 17/165; 10.3%), more frequently described in patients that received ATT (n = 13/107, 12.2%), than those that did not receive ATT (n = 4/58, 6.9%).Conclusion: In this retrospective study, addition of ATT did not have any statistically significant impact on outcome in patients with TAU.