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.

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.

Retinal microvascular signs in COVID-19.

BACKGROUND/AIMS: To explore if retinal findings are associated with COVID-19 infection. METHODS: In this prospective cross-sectional study, we recruited participants positive for COVID-19 by nasopharyngeal swab, with no medical history. Subjects underwent retinal imaging with an automated imaging device (3D OCT-1 Maestro, Topcon, Tokyo, Japan) to obtain colour fundus photographs (CFP) and optical coherence tomographic (OCT) scans of the macula. Data on personal biodata, medical history and vital signs were collected from electronic medical records. RESULTS: 108 patients were recruited. Mean age was 36.0±5.4 years. 41 (38.0%) had symptoms of acute respiratory infection (ARI) at presentation. Of 216 eyes, 25 (11.6%) had retinal signs-eight (3.7%) with microhaemorrhages, six (2.8%) with retinal vascular tortuosity and two (0.93%) with cotton wool spots (CWS). 11 eyes (5.1%) had hyper-reflective plaques in the ganglion cell-inner plexiform layer layer on OCT, of which two also had retinal signs visible on CFP (CWS and microhaemorrhage, respectively). There was no significant difference in the prevalence of retinal signs in symptomatic versus asymptomatic patients (12 (15.0%) vs 13 (9.6%), p=0.227). Patients with retinal signs were significantly more likely to have transiently elevated blood pressure than those without (p=0.03). CONCLUSION: One in nine had retinal microvascular signs on ocular imaging. These signs were observed even in asymptomatic patients with normal vital signs. These retinal microvascular signs may be related to underlying cardiovascular and thrombotic alternations associated with COVID-19 infection.

Blockchain applications in health care for COVID-19 and beyond: a systematic review.

The COVID-19 pandemic has had a substantial and global impact on health care, and has greatly accelerated the adoption of digital technology. One of these emerging digital technologies, blockchain, has unique characteristics (eg, immutability, decentralisation, and transparency) that can be useful in multiple domains (eg, management of electronic medical records and access rights, and mobile health). We conducted a systematic review of COVID-19-related and non-COVID-19-related applications of blockchain in health care. We identified relevant reports published in MEDLINE, SpringerLink, Institute of Electrical and Electronics Engineers Xplore, ScienceDirect, arXiv, and Google Scholar up to July 29, 2021. Articles that included both clinical and technical designs, with or without prototype development, were included. A total of 85 375 articles were evaluated, with 415 full length reports (37 related to COVID-19 and 378 not related to COVID-19) eventually included in the final analysis. The main COVID-19-related applications reported were pandemic control and surveillance, immunity or vaccine passport monitoring, and contact tracing. The top three non-COVID-19-related applications were management of electronic medical records, internet of things (eg, remote monitoring or mobile health), and supply chain monitoring. Most reports detailed technical performance of the blockchain prototype platforms (277 [66·7%] of 415), whereas nine (2·2%) studies showed real-world clinical application and adoption. The remaining studies (129 [31·1%] of 415) were themselves of a technical design only. The most common platforms used were Ethereum and Hyperledger. Blockchain technology has numerous potential COVID-19-related and non-COVID-19-related applications in health care. However, much of the current research remains at the technical stage, with few providing actual clinical applications, highlighting the need to translate foundational blockchain technology into clinical use.

The longitudinal psychological, physical activity, and financial impact of a COVID-19 lockdown on older adults in Singapore: The PIONEER-COVID population-based study.

BACKGROUND: Several countries have implemented 'lockdown' measures to curb the spread of the coronavirus disease 2019 (COVID-19). AIMS: To examine the psychological, physical activity (PA), and financial impact of a 2-month COVID-19 lockdown on older adults aged ≥60 years in Singapore, and to identify factors associated with adverse lockdown-related outcomes. METHOD: We interviewed 496 community-dwelling adults (mean age [standard deviation]: 73.8 [7.6] years; 54.8% female) during the lockdown who had previously participated in a population-based epidemiological study. Validated questionnaires were utilised to assess loneliness and depressive symptoms at both timepoints, while inhouse questionnaires were used to assess PA and financial difficulty during lockdown. Multivariable regression models determined the lockdown-related change in loneliness and depression scores, and the factors associated with adverse outcomes. RESULTS: Loneliness increased significantly during the lockdown period (p < 0.001) while depressive symptoms decreased (p = 0.022). Decreased PA, greater financial problems, male gender, Indian ethnicity, living alone, having a greater body mass index and perceived susceptibility to COVID-19 were all associated with worsening loneliness scores. A total of 36.9% and 19.6% participants reported decreased PA and had financial problems during the lockdown, respectively. Unemployment was associated with decreased PA, while self-employed individuals, cleaners, retail workers and smokers had greater odds of experiencing financial difficulty. CONCLUSION: Despite a decrease in depressive symptoms, our population of older Asians reported a significant increase in loneliness and decreased PA, with one-fifth experiencing financial problems during lockdown. Our data suggest that more targeted public health efforts are needed to reduce repercussions of future lockdowns.

Knowledge, attitudes, and practice towards COVID-19 among multi-ethnic elderly Asian residents in Singapore: a mixed methods study.

INTRODUCTION: We investigated knowledge, attitudes, and practice (KAP) about COVID-19 and related preventive measures in Singaporeans aged ≥ 60 years. METHODS: This was a population-based, cross-sectional, mixed-methods study (13 May 2020-9 June 2020) of participants aged ≥60 years. Self-reported KAP about ten COVID-19 symptoms and six government-endorsed preventive measures were evaluated. Multivariable regression models identified sociodemographic and health-related factors associated with knowledge, attitudes and practices in our sample. Associations between knowledge/attitude scores, and practice categories were determined using logistic regression. 78 participants were interviewed qualitatively about practice of additional preventive measures and data were analysed thematically. RESULTS: Mean awareness score of the symptoms was 7.2/10. Fever (93.0%) and diarrhoea (33.5%) were the most- and least-known symptoms, respectively. Most knew all six preventive measures (90.4%), perceived them as effective (78.7%), and practiced 'wear a mask' (97.2%). Indians, Malays, and those in smaller housing had poorer mean knowledge of COVID-19 symptoms scores. Older participants had poorer attitudes towards preventive measures. Compared to Chinese, Indians had lower odds of practicing 3/6 recommendations. A one-point increase in knowledge of and attitudes towards preventive measures score had higher odds of always practicing 3/6 and 2/6 measures, respectively. Qualitative interviews revealed use of other preventive measures, e.g. maintaining a healthy lifestyle. CONCLUSION: Elderly Singaporeans displayed high levels of KAP about COVID-19 and related preventive measures, with a positive association between levels of knowledge/attitude, and practice. However, important ethnic and socioeconomic disparities were evident, suggesting key vulnerabilities remain, requiring immediate attention.

Clinical operational considerations and responses to lockdown and reopening in the Covid-19 pandemic: experience of a tertiary ophthalmology centre in Singapore.

BACKGROUND: Much has been written on infection control and clinical measures for ophthalmic institutions and departments to cope with the COVID-19 pandemic. However, few articles have detailed implementation plans to manage lockdowns and subsequent re-openings. In this article, specific operational responses and their outcomes in a large tertiary ophthalmology centre are described. METHOD: Through a concerted effort led by a dedicated task force, the Singapore National Eye Centre (SNEC) planned and executed an operational transformation to respond to the restrictions imposed on healthcare delivery during a national lock down. A carefully calibrated re-starting of services was carried out with the subsequent phased reopening of the country, taking into consideration unique constraints faced at that time. Strategies for operating in the new normal environment were also developed. RESULTS: Outpatient attendances were safely and expediently reduced by 70% (8749 vs. 29,311) and 82% (5164 vs. 29,342) in April and May 2020, respectively, compared to the corresponding months in 2019. A correspondingly large reduction in surgical load was also achieved through a similar triaging and prioritization system. Through optimizing the center's use of space and time, as well as expanding on new models of care, a return to pre-pandemic patient load was achieved 3 months into the phased reopening of the country, and subsequently exceeded in the following months. CONCLUSION: The lessons gleaned from SNEC's experience may be useful for institutions currently facing the same challenges, and for future responses to COVID-19 resurgences or other pandemics.

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.

New digital models of care in ophthalmology, during and beyond the COVID-19 pandemic.

COVID-19 has led to massive disruptions in societal, economic and healthcare systems globally. While COVID-19 has sparked a surge and expansion of new digital business models in different industries, healthcare has been slower to adapt to digital solutions. The majority of ophthalmology clinical practices are still operating through a traditional model of 'brick-and-mortar' facilities and 'face-to-face' patient-physician interaction. In the current climate of COVID-19, there is a need to fuel implementation of digital health models for ophthalmology. In this article, we highlight the current limitations in traditional clinical models as we confront COVID-19, review the current lack of digital initiatives in ophthalmology sphere despite the presence of COVID-19, propose new digital models of care for ophthalmology and discuss potential barriers that need to be considered for sustainable transformation to take place.

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.

Digital Technology for AMD Management in the Post-COVID-19 New Normal.

PURPOSE: The COVID-19 pandemic has put strain on healthcare systems and the availability and allocation of healthcare manpower, resources and infrastructure. With immediate priorities to protect the health and safety of both patients and healthcare service providers, ophthalmologists globally were advised to defer nonurgent cases, while at the same time managing sight-threatening conditions such as neovascular Age-related Macular Degeneration (AMD). The management of AMD patients both from a monitoring and treatment perspective presents a particular challenge for ophthalmologists. This review looks at how these pressures have encouraged the acceptance and speed of adoption of digitalization. DESIGN AND METHODS: A literature review was conducted on the use of digital technology during COVID-19 pandemic, and on the transformation of medicine, ophthalmology and AMD screening through digitalization. RESULTS: In the management of AMD, the implementation of artificial intelligence and "virtual clinics" have provided assistance in screening, diagnosis, monitoring of the progression and the treatment of AMD. In addition, hardware and software developments in home monitoring devices has assisted in self-monitoring approaches. CONCLUSIONS: Digitalization strategies and developments are currently ongoing and underway to ensure early detection, stability and visual improvement in patients suffering from AMD in this COVID-19 era. This may set a precedence for the post COVID-19 new normal where digital platforms may be routine, standard and expected in healthcare delivery.

Evolving Practice Patterns in Singapore's Public Sector Ophthalmology Centers During the COVID-19 Pandemic.

Coronavirus disease 19 (COVID-19) was first reported in Wuhan, China, in December 2019, and has since become a global pandemic. Singapore was one of the first countries outside of China to be affected and reported its first case in January 2020. Strategies that were deployed successfully during the 2003 outbreak of severe acute respiratory syndrome have had to evolve to contain this novel coronavirus. Like the rest of the health care services in Singapore, the practice of ophthalmology has also had to adapt to this rapidly changing crisis. This article discusses the measures put in place by the 3 largest ophthalmology centers in Singapore's public sector in response to COVID-19, and the challenges of providing eye care in the face of stringent infection control directives, staff redeployments and "social distancing." The recently imposed "circuit breaker," effectively a partial lockdown of the country, has further limited our work to only the most essential of services. Our staff are also increasingly part of frontline efforts in the screening and care of patients with COVID-19. However, this crisis has also been an opportunity to push ahead with innovative practices and given momentum to the use of teleophthalmology and other digital technologies. Amidst this uncertainty, our centers are already planning for how ophthalmology in Singapore will be practiced in this next stage of the COVID-19 pandemic, and beyond.