Test, Trace, and Put on the Blockchain?: A Viewpoint Evaluating the Use of Decentralized Systems for Algorithmic Contact Tracing to Combat a Global Pandemic

Integrating blockchain technology with artificial intelligence for the diagnosis of tibial plateau fractures

PURPOSE

The application of artificial intelligence (AI) in healthcare has seen widespread implementation, with numerous studies highlighting the development of robust algorithms. However, limited attention has been given to the secure utilization of raw data for medical model training, and its subsequent impact on clinical decision-making and real-world applications. This study aims to assess the feasibility and effectiveness of an advanced diagnostic model that integrates blockchain technology and AI for the identification of tibial plateau fractures (TPFs) in emergency settings.

METHOD

In this study, blockchain technology was utilized to construct a distributed database for trauma orthopedics, images collected from three independent hospitals for model training, testing, and internal validation. Then, a distributed network combining blockchain and deep learning was developed for the detection of TPFs, with model parameters aggregated across multiple nodes to enhance accuracy. The model's performance was comprehensively evaluated using metrics including accuracy, sensitivity, specificity, F1 score, and the area under the receiver operating characteristic curve (AUC). In addition, the performance of the centralized model, the distributed AI model, clinical orthopedic attending physicians, and AI-assisted attending physicians was tested on an external validation dataset.

RESULTS

In the testing set, the accuracy of our distributed model was 0.9603 [95% CI (0.9598, 0.9605)] and the AUC was 0.9911 [95% CI (0.9893, 0.9915)] for TPF detection. In the external validation set, the accuracy reached 0.9636 [95% CI (0.9388, 0.9762)], was slightly higher than that of the centralized YOLOv8n model at 0.9632 [95% CI (0.9387, 0.9755)] (p > 0.05), and exceeded the orthopedic physician at 0.9291 [95% CI (0.9002, 0.9482)] and radiology attending physician at 0.9175 [95% CI (0.8891, 0.9393)], with a statistically significant difference (p < 0.05). Additionally, the centralized model (4.99 ± 0.01 min) had shorter diagnosis times compared to the orthopedic attending physician (25.45 ± 1.92 min) and the radiology attending physician (26.21 ± 1.20 min), with a statistically significant difference (p < 0.05).

CONCLUSION

The model based on the integration of blockchain technology and AI can realize safe, collaborative, and convenient assisted diagnosis of TPF. Through the aggregation of training parameters by decentralized algorithms, it can achieve model construction without data leaving the hospital and may exert clinical application value in the emergency settings.

Security of Cryptocurrencies: A View on the State-of-the-Art Research and Current Developments

[Context] The goal of security is to protect digital assets, devices, and services from being disrupted, exploited or stolen by unauthorized users. It is also about having reliable information available at the right time. [Motivation] Since the inception in 2009 of the first cryptocurrency, few studies have been undertaken to analyze and review the state-of-the-art research and current developments with respect to the security of cryptocurrencies. [Purpose] We aim to provide both theoretical and empirical insights into the security landscape, in particular focusing on both technical solutions and human-related facets. [Methodology] We used an integrative review which could help in building science and scholarly research, the basis for conceptual and empirical models. [Results] Successful defense against cyberattacks depends on technical measures on the one hand, as well as on self-education and training with the aim to develop competence, knowledge, skills and social abilities, on the other. [Contribution] Our findings provide a comprehensive review for the major achievements and developments of the recent progress on the security of cryptocurrencies. [Future research] Since there is increasing interest in adoption of the current solutions within the central bank digital currencies, the future research should explore the development and inception of effective measures against social engineering attacks, which still remain the main concern.

Tracing app technology: an ethical review in the COVID-19 era and directions for post-COVID-19

We conducted a systematic literature review on the ethical considerations of the use of contact tracing app technology, which was extensively implemented during the COVID-19 pandemic. The rapid and extensive use of this technology during the COVID-19 pandemic, while benefiting the public well-being by providing information about people's mobility and movements to control the spread of the virus, raised several ethical concerns for the post-COVID-19 era. To investigate these concerns for the post-pandemic situation and provide direction for future events, we analyzed the current ethical frameworks, research, and case studies about the ethical usage of tracing app technology. The results suggest there are seven essential ethical considerations-privacy, security, acceptability, government surveillance, transparency, justice, and voluntariness-in the ethical use of contact tracing technology. In this paper, we explain and discuss these considerations and how they are needed for the ethical usage of this technology. The findings also highlight the importance of developing integrated guidelines and frameworks for implementation of such technology in the post- COVID-19 world.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10676-022-09659-6.

On Deploying Blockchain Technologies in Supply Chain Strategies and the COVID-19 Pandemic: A Systematic Literature Review and Research Outlook

The emergence of a new pandemic, known as COVID-19, has touched various sections of the supply chain (SC). Since then, numerous studies have been conducted on the issue, but the need for a holistic review study that highlights the gaps and limits of previous research, as well as opportunities and agendas for future studies, is palpable. Through a systematic literature review on blockchain technology (BCT) deployment in supply-chain management (SCM) concerning the COVID-19 pandemic, this research seeks to add to the content of previous studies and to enlighten the path for future studies. Relevant papers were found using a variety of resources (Scopus, Google Scholar, Web of Science, and ProQuest). Seventy-two articles were systematically selected, considering the PRISMA procedure, and were thoroughly analyzed based on BCT, methodologies, industrial sectors, geographical, and sustainability context. According to our findings, there is a significant lack of empirical and quantitative methodologies in the literature. The majority of studies did not take specific industries into account. Furthermore, the articles focusing on the sustainability context are few, particularly regarding social and environmental issues. In addition, most of the reviewed papers did not consider the geographical context. The results indicate that the deployment of BCT in several sectors is not uniform, and this utilization is reliant on their services during the COVID-19 pandemic. Furthermore, the concentration of research on the impacts of the BCT on SCM differs according to the conditions of various countries in terms of the consequences of the COVID-19 pandemic. The findings also show that there is a direct relationship between the deployment of BCT and sustainability factors, such as economic and waste issues, under the circumstances surrounding COVID-19. Finally, this study offers research opportunities and agendas to help academics and other stakeholders to gain a better knowledge of the present literature, recognize aspects that necessitate more exploration, and drive prospective studies.

Appraisal of a Contact Tracing Training Program for COVID-19 in Greece Focusing on Vulnerable Populations

BACKGROUND

Contact tracing as an epidemiological strategy has repeatedly contributed to the containment of various past epidemics and succeeded in controlling the spread of disease in the community. Systematic training of contact tracers is crucial in ensuring the effectiveness of epidemic containment.

METHODS

An intensive training course was offered to 216 health and other professionals who work with vulnerable population groups, such as Roma, refugees, and migrants in Greece, by the scientific team of the postgraduate programme "Global Health-Disaster Medicine" of the Medical School, National and Kapodistrian University of Athens, with the support of the Swiss embassy in Greece. The course was delivered online due to the pandemic restriction measures and was comprised of 16 h over 2 days. The course curriculum was adapted in Greek using, upon agreement, a similar training course to what was developed by the Johns Hopkins University Bloomberg School of Public Health. Evaluation of the course was conducted in order to determine the short term satisfaction from participating in this training course.

RESULTS

A total of 70% of the course participants completed the evaluation questionnaires and all trainers gave feedback on the course. The training modules were ranked as extremely useful by the majority of the participants and over 50% of the participants specifically stated that the course content was directly related to their work with vulnerable groups. Content about the ethics of contact tracing and the effective communication skills presented were deemed most useful.

CONCLUSION

The course was well organised and provided the required skills for effective contact tracing. Many course participants intend to use some components in their work with vulnerable populations groups. Contact tracing efforts work best in a systematic and coordinated way and the provision of systematic and organised training can greatly increase its effectiveness.