Search

Artificial intelligence (AI) has witnessed significant advancements, reshaping various industries, including healthcare. The introduction of ChatGPT by OpenAI in November 2022 marked a pivotal moment, showcasing the potential of generative AI in revolutionising patient care, diagnosis and treatment. Generative AI, unlike traditional AI systems, possesses the ability to generate new content by understanding patterns within datasets. This article explores the evolution of AI in healthcare, tracing its roots to the term coined by John McCarthy in 1955 and the contributions of pioneers like John Von Neumann and Alan Turing. Currently, generative AI, particularly Large Language Models, holds promise across three broad categories in healthcare: patient care, education and research. In patient care, it offers solutions in clinical document management, diagnostic support and operative planning. Notable advancements include Microsoft's collaboration with Epic for integrating AI into electronic medical records (EMRs), enhancing clinical data management and patient care. Furthermore, generative AI aids in surgical decision-making, as demonstrated in plastic, orthopaedic and hepatobiliary surgeries. However, challenges such as bias, hallucination and integration with EMR systems necessitate caution and ongoing evaluation. The article also presents insights from the implementation of NUHS Russell-GPT, a generative AI chatbot, in a hand surgery department, showcasing its utility in administrative tasks but highlighting challenges in surgical planning and EMR integration. The survey showed unanimous support for incorporating AI into clinical settings, with all respondents being open to its use. In conclusion, generative AI is poised to enhance patient care and ease physician workloads, starting with automating administrative tasks and evolving to inform diagnoses, tailored treatment plans, as well as aid in surgical planning. As healthcare systems navigate the complexities of integrating AI, the potential benefits for both physicians and patients remain significant, offering a glimpse into a future where AI transforms healthcare delivery. Level of Evidence: Level V (Diagnostic) [ABSTRACT FROM AUTHOR]

While energy risk is increasingly recognized as a systemic risk, there is limited comprehensive analysis of the risk propagation in regional contexts. In this study, we examine oil and natural gas price changes and shocks in relation to equity market returns and volatility for 24 European Economic Area (EEA) countries. In addition to traditional panel regressions, we also deploy the Diebold‐Yilmaz (2014) spillover index for a closed network analysis. We differentiate in the cross‐section across the core EU block, PIIGS countries, EU enlargement countries joining after 2004, and other non‐EU countries, to provide insights into the ongoing debates on the European energy market stability. While we find evidence of the manifestation of energy risk throughout the sample period, we find that until 2019 the primary sources of volatility spillover in the EEA economic network arose from economic or political uncertainty. Energy risks, measured by large crude oil and natural gas price shocks also significantly contributed to equity market volatility, with increasing volatility risk arising from natural gas, a green labelled energy source after 2019. Last, we show that CEEC equity markets are more sensitive to oil and natural gas price shocks when domestic currencies depreciate against the Euro. [ABSTRACT FROM AUTHOR]

Public sector innovation is crucial for smart city development. This paper compares progress in Singapore and Hong Kong (HK). Although similarly competitive in many areas, SG is ahead of HK in rankings. Why does this disparity exist? What forms of public sector innovation are crucial for smart city development? This paper answers these questions for policy-makers by examining the role of public sector innovation in driving smart city developments, and underscores the importance of research and development within the public sector. ABSTRACT Since the 2000s, Hong Kong (HK) and Singapore (SG) have been working to reinvent themselves as smart cities. Despite their similarities, SG has consistently ranked ahead of HK on several smart city indices. To explain this gap, the smart city initiatives of both cities were categorized using a six-factor typology of public sector innovation. Further analysis indicated that SG was ahead of HK because its government has been more aggressive in funding and fostering innovation. This paper suggests that a government's financial support for public sector innovation, as well as its ability to redirect resources within the public sector and get citizens involved, will catalyse transformational efforts into a smart city. [ABSTRACT FROM AUTHOR]

Policy risk, rather than information asymmetry, explains the cross-sectional underpricing of privatized initial public offerings. The issuer governments of high policy risk issues tend to retain a large equity stake and underprice more with underpricing increasing in retained equity. While the issuer government's retained equity is an observable signal for policy risk, we find that the quality of a country's bureaucratic machinery is a more intuitive and practical measure of policy risk. Policy risk also explains the absence of a systematic relation between the initial returns on privatized and private initial public offerings. [ABSTRACT FROM AUTHOR]