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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]

In this study, the relationship between electricity and growth of the economy is investigated by applying the newly-developed bootstrap autoregressive-distributed lag test with a Fourier function to examine both the causality and cointegration for China, India, and the United States (US). While it is not possible to detect a long-term cointegration relation among the economy's electricity and growth, the study findings demonstrate the contingency of the causality. The ensemble method in machine learning performs better than conventional methods as electricity is an independent indicator for forecast economics. Concerning the US, previous electricity consumption has a positive impact on the current nature of economic growth. In contrast, the consumption of electricity is negatively affected by the development of the economy. However, for China and India, positive and negative feedback can be observed, respectively. Due to the increased awareness of the environment's adverse effects, China should promote technologies that conserve energy and boost energy efficiency to achieve sustainable development in both environmental and economic terms. In India's context, broadening access to electricity has significance for residents in rural areas and enhances economic growth. It is recommended that policy-makers promote innovative technologies in the US, as the abundant natural and human resources can make valuable contributions to the society and development of the economy. [ABSTRACT FROM AUTHOR]