Search

Introduction: The emergence of artificial intelligence (AI) chat programs has opened two distinct paths, one enhancing interaction and another potentially replacing personal understanding. Ethical and legal concerns arise due to the rapid development of these programs. This paper investigates academic discussions on AI in medicine, analyzing the context, frequency, and reasons behind these conversations. Methods: The study collected data from the Web of Science database on articles containing the keyword "ChatGPT" published from January to September 2023, resulting in 786 medically related journal articles. The inclusion criteria were peer-reviewed articles in English related to medicine. Results: The United States led in publications (38.1%), followed by India (15.5%) and China (7.0%). Keywords such as "patient" (16.7%), "research" (12%), and "performance" (10.6%) were prevalent. The Cureus Journal of Medical Science (11.8%) had the most publications, followed by the Annals of Biomedical Engineering (8.3%). August 2023 had the highest number of publications (29.3%), with significant growth between February to March and April to May. Medical General Internal (21.0%) was the most common category, followed by Surgery (15.4%) and Radiology (7.9%). Discussion: The prominence of India in ChatGPT research, despite lower research funding, indicates the platform's popularity and highlights the importance of monitoring its use for potential medical misinformation. China's interest in ChatGPT research suggests a focus on Natural Language Processing (NLP) AI applications, despite public bans on the platform. Cureus' success in publishing ChatGPT articles can be attributed to its open-access, rapid publication model. The study identifies research trends in plastic surgery, radiology, and obstetric gynecology, emphasizing the need for ethical considerations and reliability assessments in the application of ChatGPT in medical practice. Conclusion: ChatGPT's presence in medical literature is growing rapidly across various specialties, but concerns related to safety, privacy, and accuracy persist. More research is needed to assess its suitability for patient care and implications for non-medical use. Skepticism and thorough review of research are essential, as current studies may face retraction as more information emerges. [ABSTRACT FROM AUTHOR]

Questions abound over how universities should teach and prepare the next generation of researchers to confront current and future wicked problems. With so much focus on curriculum and training, it is crucial that we step back and reflect on higher education's capabilities to foster solution-oriented, collaborative research. What do the institutional incentive structures in higher education support, in terms of practices and outputs related to scholarship? And are those structures felt evenly across the academy? Those doing research in these spaces—in terms of title, autonomy, power, privilege, and status—vary widely by their institutional locations as well as in terms of their ties to broader disciplinary norms. To assess whether these dynamic, contested institutional landscapes afford so-called wicked problem scholarship, this paper draws from survey and interview data collected from 44 researchers working at the nexus of food, energy, and water systems at Carnegie Research 1 universities in the United States. Findings point to an uneven institutional landscape, which is shown to shape in different ways the type of solutions-oriented, collaborative scholarship fostered across the five positions examined. The paper concludes by reflecting on the paper's findings, particularly in terms of what the data tell us about higher education as a place that fosters wicked problems scholarship, while also highlighting the study's limitations. [ABSTRACT FROM AUTHOR]

In most of the United States, insurance companies may use gender to determine car insurance rates. In addition, several studies have shown that women over the age of 25 generally pay more than men for car insurance. Then, we investigate whether the distributions of claims for women and men differ in location, scale and shape by means of the GAMLSS regression framework, using microdata provided by U.S. and Australian insurance companies, to use this evidence to support policy makers' decisions. We also develop a parametric-bootstrap test to investigate the tail behavior of the distributions. When covariates are not considered, the distribution of claims does not appear to differ by gender. When covariates are included, the regressions provide mixed evidence for the location parameter. However, for female claimants, the spread of the distribution is lower. Our research suggests that, at least for the contexts analyzed, there is no clear statistical reason for charging higher rates to women. While providing evidence to support unisex insurance pricing policies, given the limitations represented by the use of country-specific data, this paper aims to promote further research on this topic with different datasets to corroborate our findings and draw more general conclusions. [ABSTRACT FROM AUTHOR]

Copyright of Maternal & Child Health Journal is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the United States, recent changes to the National Statistical System have amplified the geographic-demographic resolution trade-off. That is, when working with demographic and economic data from the American Community Survey, as one zooms in geographically one loses resolution demographically due to very large margins of error. In this paper, we present a solution to this problem in the form of an AI based open and reproducible geodemographic classification system for the United States using small area estimates from the American Community Survey (ACS). We employ a partitioning clustering algorithm to a range of socio-economic, demographic, and built environment variables. Our approach utilizes an open source software pipeline that ensures adaptability to future data updates. A key innovation is the integration of GPT4, a state-of-the-art large language model, to generate intuitive cluster descriptions and names. This represents a novel application of natural language processing in geodemographic research and showcases the potential for human-AI collaboration within the geospatial domain. [ABSTRACT FROM AUTHOR]

The growing prevalence of cardiovascular diseases in the United States (US) has disproportionately affected minority populations more than their white counterparts. A population that is often overlooked is the Asian American population, particularly Southeastern Asian immigrants. Despite having relatively favorable socioeconomic indicators compared to the general US population, Asian Americans, specifically Southeast Asian individuals, face a significant burden of traditional cardiovascular risk factors and are considered a high cardiovascular disease risk group. In addition, most studies have aggregated Asian populations into one major racial group rather than analyzing the different ethnicities among the Asian categorization. While some studies suggest that the acculturation process has some degree of impact on cardiovascular health, there has not been a widely-used tool to measure or ascertain the totality of acculturation. Instead, multiple proxies have been used to measure acculturation, and prior studies have argued for more culturally-tailored acculturation proxies. This paper aims to assess the implications of different acculturation measures on cardiovascular health among Asian Americans, particularly Southeastern Asian immigrants. The following proxies were expanded on in this paper: English spoken at home, length of stay in the US, religiosity and spirituality, and admixed family structures. Previous studies showed that as the length of stay in the US increases, the burden of cardiovascular risk factors increases. However, the impact of English spoken at home, religiosity, and admixed family structure are still inconclusive given the extent of current studies. While most studies suggest that an increase in acculturation increases the risk of cardiovascular disease, it is critical to note that acculturation is a multifaceted process. Therefore, more studies are necessary to appropriately examine the implications of various acculturation processes on cardiovascular risk factors in Asians, specifically Southeastern Asian individuals in the US. [ABSTRACT FROM AUTHOR]

Transportation practitioners and scholars increasingly view car-free mobility as an essential component of a sustainable, healthy, and safe transportation future. In the United States, however, strikingly few households—only around 9%—do not own cars. Moreover, most zero-vehicle individuals—around 80%—are without vehicles due of constraint (e.g., because they cannot afford one), while a much smaller fraction—around 20%—are car-free because they can meet their mobility needs without one. This latter group is of interest to transportation researchers and practitioners, given the imperative to reduce driving and its associated negative externalities. In this paper, I examine factors that contribute to individuals' decisions to live car-free. This research is based on 430 comments posted on the social content-sharing website Reddit, in which commenters shared their first-hand experiences related to the prospect of going car-free. These comments were obtained from 46 threads situated in seven different US cities, focusing specifically on car ownership decisions. Commenters described accessible neighborhoods as foundational to decisions to forego a vehicle. While such conditions were typically necessary, however, they sometimes were not sufficient to foster car-free choices. Costs of car ownership, especially parking costs, were often the deciding factor for commenters who opted not to have a car. Finally, inconveniences related to car ownership and travel, like traffic-related stress, were discussed as benefits of living car-free. In sum, the observed individual decisions about car ownership tend to consist of people balancing supportive conditions for non-car travel against costs of and constraints on car-travel. [ABSTRACT FROM AUTHOR]

This paper addresses the notion of electronic economics by examining financial technology (fintech) firms' performance and corporate governance quality, using data from the United States. The findings support our maintained assumption that due to the economics of electronic platforms perused by financial technology firms, these firms outperform firms from other industries (non-Fintech). The final sample comprises 1,712 company-year observations between 2010 and 2019 (pre-COVID-19). The evidence suggests that our corporate governance quality index, developed from Organisation of Economic Cooperation and Development (www.oecd.org/corporate/corporate-governance-factbook.htm, 2019) guidelines, accurately captures corporate governance quality in the United States, principally due to the inclusion of an anti-bribery policy indicator, in the index. The results suggest that this evidence is not merely an artefact due to the corporate governance quality index potentially capturing priced risk factors. Our findings reveal that fintech firms have superior corporate governance quality than non-fintech and that fintech firms place more reliance on internal versus external corporate governance mechanisms, vis-a-vis companies in other industries. [ABSTRACT FROM AUTHOR]

An initial and comprehensive map of ecological regions across the conterminous United States was provided by Omernik in 1987. Because that paper was the most-cited published by the Annals of the American Association of Geographers, we sought to assess and quantify its contribution to science. To do so, we conducted a scientometric analysis to address the following main questions: 1) What are the temporal and spatial citation trends? We expected that Omernik's paper would still be employed 36 years after its publication, and mostly in the United States of America. 2) For what types of environments and organisms has it been applied? Based on its generality, we expected that it had been applied to both terrestrial and aquatic ecosystems. 3) What are the main applications of Omernik's article? We predicted that it would mostly be used for describing and delineating study sites and management areas, as well as for selecting regional reference sites. The number of citations presented a positive temporal increase, indicating its continued applicability. Most papers dealt with aquatic environments, mainly in streams carried out predominantly in the United States of America, as was one of its earliest applications. The usefulness of ecoregions for assessing and managing biotic and abiotic patterns and distributions were the main topics addressed by scientists. Ecoregions have offered a general framework for developing regional expectations and rational regional management policies across large areas, as was their original intent. In addition, ecoregion maps were used for communicating patterns—or the lack of them—to interested scientists, citizens, and decision-makers. That comprehensiveness of Omernik's ecoregion approach has led to its widespread applicability and continued usefulness to a diverse set of scientific and management disciplines. [ABSTRACT FROM AUTHOR]

Nested Benders's decomposition is an efficient means to solve large-scale optimization problems with a natural time sequence of decisions. This paper examines the use of the technique to decompose and solve efficiently capacity-expansion problems for electricity systems with hydroelectric and renewable generators. To this end we develop an archetypal planning model that captures key features of hydroelectric and renewable generators and apply it to a case study that is based on the Columbia River system in the northwestern United States of America. We apply standard network and within-year temporal simplifications to reduce the problem's size. Nevertheless, the remaining problem is large-scale and we demonstrate the use of nested Benders's decomposition to solve it. We explore refinements of the decomposition method which yield further performance improvements. Overall, we show that nested Benders's decomposition yields good computational performance with minimal loss of model fidelity. [ABSTRACT FROM AUTHOR]