Effects Of Artificial Intelligence Research Articles

Effects of Artificial Intelligence and Virtual Reality in Martial Arts Sports on Students’ Physical and Mental Health

As a treasure left over from Chinese traditional culture, martial arts have a long history and lasts for a long time. With the country’s promotion and support of martial arts culture, martial arts have also attracted more and more people’s attention. In order to carry forward the martial arts culture, the combination of martial arts and sports has formed a set of martial arts sports suitable for today’s students, such as martial arts aerobics. It is used as a class exercise for students, and basically, every student in the school has learned it and practiced it often. However, with the development of the times, it is difficult for today’s students to arouse students’ enthusiasm for martial arts sports for traditional martial arts sports. Artificial intelligence technology and virtual reality, as products of today’s digital age, attract the attention and use of students with their unique features. This also means that the reform of martial arts sports based on artificial intelligence and virtual reality technology is imperative in order to make more students regain their enthusiasm for martial arts sports. However, the specific impact of artificial intelligence and virtual reality on the physical and mental development of students in martial arts sports is a problem to be confirmed by research. Through in-depth research on artificial intelligence and virtual reality technology, this paper shows that artificial intelligence and virtual reality martial arts sports can increase the lung capacity of boys by about 14% and girls by 16%; the effect on physical fitness can increase the lower body strength of boys by 3% and the flexibility of girls by 30%; as for the impact on mental health, it can be concluded that the emotional and cognitive dimensions of boys and girls have increased by about 19% compared with the previous values.

Effectiveness of Artificial Intelligence (AI) in Improving Pupils' Deep Learning in Primary School Mathematics Teaching in Fujian Province.

Several primary school students in Fujian Province have perceived studying mathematics as challenging. To deal with this issue, computer technology advancements, specifically artificial intelligence (AI), present an opportunity to evaluate individual students' learning challenges and give individualized support to optimize their success in mathematics classes. It is also possible to use virtual reality (VR) to assist learners in acquiring complex mathematical and logical ideas and to lessen learners' mistakes. As a result, researchers, particularly beginners, are missing out on a complete perspective of the study of AI in teaching mathematics. That is why we are exploring the role of AI in math education by developing a “fuzzy-based tweakable convolution neural network with a long short-term memory (FT-CNN-LSTM-AM)” method. For this investigation, the students' datasets are taken and educated by mathematical teaching via the application of AI. The proposed method is utilized to predict the students' performance in mathematical education. A grey wolf optimizer is employed to boost the effectiveness of the proposed method. Furthermore, the performance of the proposed method is analyzed and compared with existing approaches to gain the highest reliability.

Artificial intelligence and unemployment:An international evidence

This paper examines the possible effect of artificial intelligence (AI) on unemployment using a broad database of AI-related patents in 40 developed and developing markets from 2000 to 2019. The study employs a panel smooth transition regression (PSTR) model to analyse the relationship between artificial intelligence and unemployment under various inflation levels. The study contributes to the existing literature with several findings. First, results from our analysis confirm the non-linear relationship between artificial intelligence and unemployment depending on the threshold of inflation. In general, artificial intelligence increases unemployment until a certain inflation threshold is attained, and then the effect reduces afterwards. Second, the smooth mechanism employed in this analysis can capture individual estimates varying amongst countries over time.

The Effect of Artificial Intelligence on End-User Online Purchasing Decisions: Toward an Integrated Conceptual Framework

This study was an investigation into the effect of selected artificial intelligence tools and the consideration set on the end-user purchasing intentions of convenient and shopping products of Saudi Arabian customers. The consideration set was the factor that the researcher sought to associate directly with the online purchasing intention variable. The selected AI tools and approaches were machine learning, purchase duration, social product recommendation, and social media dependency. The four served as the indirect factors, as their effect was measured against the consideration set variable. The theoretical framework employed in this study comprised the unified theory of acceptance and use of technology (UTAUT) and the theory of reasoned action. The researchers used an online survey with a sample of 148 customers. In analyzing the findings, the researchers opted for the structural equation modeling (SEM) approach. The findings indicated evidence of association with a consideration set of three independent variables, namely, machine learning, purchase duration, and product recommendation. The study also established that customer consideration sets influence end-user purchase decisions for online customers.

Effect of artificial intelligence on the modernization of nursing practice

This research performs a systematic review on the impact of artificial intelligence on the modernization of nursing. The key types of artificial intelligence in the research are clinical decision support systems, mobile health, sensor-based technologies, voice assistants, and robotics. The study will cover all geographical locations and all nursing fields. Sources of data for the research journal articles and clinical studies reports on the impact of artificial intelligence in nursing. Information will be extracted from various databases such as PubMed, Google scholar, and clinicaltrials.gov. A quantitative and qualitative analysis of the data collected will be conducted to reach findings that are free from bias.

Can Application of Artificial Intelligence in Enterprises Promote the Corporate Governance?

The impact of artificial intelligence (AI) on the economy and industry has gradually extended from the macroeconomic to the microeconomic level. Artificial intelligence technology has brought great innovation and impact to the company’s operation and management and has a strong role in promoting the level of corporate governance. Based on an in-depth analysis of the theoretical mechanism of artificial intelligence affecting corporate governance, and based on the balanced panel data of Chinese A-share listed companies from 2011 to 2020, this paper empirically analyzes the mechanism and intermediary effect of artificial intelligence affecting corporate governance. The study found that AI applications can significantly improve corporate governance levels, and a higher level of artificial intelligence application can produce a higher level of corporate governance. From the perspective of the impact path, artificial intelligence technology can significantly improve the degree of information symmetry required for corporate governance, thereby providing favorable technical conditions and decision support for improving the level of corporate governance. Artificial intelligence technology has a positive and effective impact on corporate governance through the information symmetry effect.

Abstract 4087: Developing a standardized framework for curating oncology datasets generated by manual abstraction and artificial intelligence

Abstract Background: The widespread uptake of electronic health records (EHRs) has made the creation of custom, real-world datasets for research more feasible. As a result, multiple research datasets with overlapping populations are often generated, using different methodologies, and frequently siloed within and between research groups, limiting the scope of the data’s use. Currently, there is no standard for collating and evaluating such data. Using existing lung oncology datasets, we developed an approach to determine optimal methods of combining and curating clinical data from different sources. Methods: Two separate study datasets containing data for lung cancer patients diagnosed and/or treated within Princess Margaret Cancer Centre (PM, Toronto) were investigated. Study 1 manually abstracted clinical data for 1,990 patients, first seen at PM between 2014-2016; Study 2 leveraged the artificial intelligence engine, DARWEN™, to extract clinical data directly from EHRs for 4,466 patients, diagnosed between 2014-2018. Each dataset was individually assessed for internal consistency before comparing the overlapping population (Test Group, n=1892) to identify, investigate, and resolve differences. Patterns of data extraction performance were evaluated to define optimal methods for combining datasets and informing future data collection. Herein, epidermal growth factor receptor (EGFR) mutation status is used as an illustrative example. Results: Study 1 and 2 had similar distributions of clinicodemographic data and frequency of EGFR mutations. The Test Group had 100% agreement for date of birth, and >99% agreement for sex, with all discrepancies resulting from human error in Study 1. The Test Group had a 98% agreement for EGFR positivity and 98-99% agreement for specific exon mutations. Of the 106 disagreements for specific mutations, 50% (n=53) were due to Study 1 human error. Study 2 prioritized specificity over sensitivity for biomarker extraction, resulting in more false negatives (25% of errors, n=26). As DARWEN™ only extracted EGFR data from pathology reports, 18% (n=19) of discrepancies were due to lack of access to relevant information captured elsewhere in patients’ EHRs. Adjudicators could not resolve the remaining 7% of disagreements (n=8). Conclusions: By comparing overlapping datasets, the strengths and weaknesses of each study design and extraction methodology were identified. This process demonstrated the effectiveness of artificial intelligence for extracting accurate patient-level clinicodemographic and mutation status data from EHRs, and the value of targeted manual chart review. Our approach provides a roadmap for leveraging existing clinical datasets to their fullest potential, which is relevant across diverse data extraction methods and study designs. Citation Format: Benjamin M. Grant, Aein Zarrin, Luna Zhan, Rami Ajaj, Lina Darwish, Khaleeq Khan, Devalben Patel, Kaitlyn Chiasson, Karmugi Balaratnam, Maisha T. Chowdhury, Amir-Arsalan Sabouhanian, Joshua Herman, Preet Walia, Evan Strom, Catherine Brown, Miguel Garcia-Pardo, Sabine Schmid, Christopher Pettengell, Erin L. Stewart, Geoffrey Liu. Developing a standardized framework for curating oncology datasets generated by manual abstraction and artificial intelligence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4087.

Effects of artificial intelligence on duopoly competition

ABSTRACT This article highlights duopoly competition with artificial intelligence (AI) technology. With game theory model, some interesting conclusions are obtained. On one hand, high-cost firms have more intention to invest AI. On the other hand, AI reduces output difference while promotes consumer surplus.

An appraisal of ethical issues and the effect of artificial intelligence on the cryptocurrency market

The world has gradually embraced Cryptocurrency at various levels of capacity and it is not governed or regulated by any Control system. It has over time been used by participants as a means to invest despite the volatility of the market. Though Government does not have the means to outright stop the virtual marketing deals of Cryptocurrency, recently Nigerian government called for deposit money banks to close all corresponding accounts which are perceived to be involved in Cryptocurrency trading. The Crypto market has evolved as the digital and internet world exponentially evolved. Sadly, Cryptocurrency has been misused by illegal participants and exploited wrongly which has caused a lot of worrisome issues around the world like loss of funds, hacking of financial databases, terrorist financing, and identity fraud. This paper aims to identify the methodology surrounding the world of Cryptocurrency and how advancement in technology through artificial intelligence can help solve ethical issues related to cryptocurrency trading. Based on these appraisals, we highlighted procedures to provide a safer, secure, and relatable market for every interested individual.

An appraisal of ethical issues and the effect of artificial intelligence on the cryptocurrency market

An appraisal of ethical issues and the effect of artificial intelligence on the cryptocurrency market

Macroeconomic effects of artificial intelligence on emerging economies: Insights from Bangladesh

Artificial intelligence (AI) has the potential to increase economic growth substantially across the world. This paper explores the predicted potentials of AI from macroeconomic perspectives, employing theoretical analysis and contextualizing Bangladesh. The study employs time series data to examine the effects of AI on the labor market and productivity. The findings indicate that Bangladesh was yet to realize the expected economic merits though the integrated number of AI-induced industry robots has been insignificant. For AI to be effective in Bangladesh, the country shall adopt more AI robots across the various sectors, mainly manufacturing and service. Besides, the country may complement the human labor force with AI labor instead of relying on only one as a source of labor.

Effects of Artificial Intelligence on Caries Therapy Selection

Effects of Artificial Intelligence on Caries Therapy Selection

An evaluation of information online on artificial intelligence in medical imaging

BackgroundOpinions seem somewhat divided when considering the effect of artificial intelligence (AI) on medical imaging. The aim of this study was to characterise viewpoints presented online relating to the impact of AI on the field of radiology and to assess who is engaging in this discourse.MethodsTwo search methods were used to identify online information relating to AI and radiology. Firstly, 34 terms were searched using Google and the first two pages of results for each term were evaluated. Secondly, a Rich Search Site (RSS) feed evaluated incidental information over 3 weeks. Webpages were evaluated and categorized as having a positive, negative, balanced, or neutral viewpoint based on study criteria.ResultsOf the 680 webpages identified using the Google search engine, 248 were deemed relevant and accessible. 43.2% had a positive viewpoint, 38.3% a balanced viewpoint, 15.3% a neutral viewpoint, and 3.2% a negative viewpoint. Peer-reviewed journals represented the most common webpage source (48%), followed by media (29%), commercial sources (12%), and educational sources (8%). Commercial webpages had the highest proportion of positive viewpoints (66%). Radiologists were identified as the most common author group (38.9%). The RSS feed identified 177 posts of which were relevant and accessible. 86% of posts were of media origin expressing positive viewpoints (64%).ConclusionThe overall opinion of the impact of AI on radiology presented online is a positive one. Consistency across a range of sources and author groups exists. Radiologists were significant contributors to this online discussion and the results may impact future recruitment.

Evaluation of Accounting Data of Water Company Based on Combination Model

Driven by the dual effects of artificial intelligence and accounting transformation, it has become one of the research hotspots of accounting intelligence in China to replace accountants with computers to make professional judgments and automatically evaluate accounting. On the basis of summarizing and analyzing the research status in the field of intelligent accounting, the realization path of intelligent accounting in water companies is put forward in this paper. By introducing the improved Apriori learning algorithm based on Boolean mapping matrix, intelligent data mining is carried out for evaluation of water accounting. With the help of the improved attribute inductive learning algorithm, the corresponding relationship between the original water consumption attribute and the water right transaction is mined and output. In addition, with the help of forward reasoning in inference engine technology, the computer intelligent data evaluation function is realized. Finally, the functional architecture of accounting system of the water company is designed, which provides reference for the development and application of intelligent accounting system, and explores a new path for the integration of accounting and intelligent algorithms.

Effect of Artificial Intelligence on End-to-End Customer Centric Business Model

Effect of Artificial Intelligence on End-to-End Customer Centric Business Model

Digital innovation and the effects of artificial intelligence on firms’ research and development – Automation or augmentation, exploration or exploitation?

Digitalization has altered many assumptions underpinning research on innovation management. At the early innings of exploring how digital innovation management stands out, there is a need for further studies in this area. Previous research on how firms use artificial intelligence has distinguished between automation and augmentation of human activities. In this paper, we explore how firms implement artificial intelligence within research and development. Utilizing an international news database spanning 956 articles from 122 newspapers published in 2020, we find that artificial intelligence is primarily adopted to augment human activities (55%) within research and development, rather than to automate matters (11%). We observe differences across sectors where automation is more common in government, information and communication technology (ICT), and technology and software. Our systematic coding shows that artificial intelligence is primarily adopted for exploration research and development (64%), rather than exploitation (5%). Based on these findings, we conclude that research and development from artificial intelligence primarily focuses on novel markets and areas of operations, rather than enhancing existing product markets and activities. Moreover, it augments human labor rather than replaces it; hence, job losses related to artificial intelligence do not seem to be taking place within research and development.

The Effect of Artificial Intelligence on the Nutritional Status of Children After Cardiac Surgery: Randomized Controlled Trial

Background Malnutrition is the most common problem in congenital heart disease patients. Health-based mobile apps play an important role in the planning and tracking of diet for better nutritional status. Objective The aim of this paper was to assess the effect of artificial intelligence on the nutritional status of children after cardiac surgery in comparison to the usual care group. We also aimed to assess the usefulness of a diet-related mobile app in comparison to the usual care group. Methods This is a two-arm randomized controlled trial, which was conducted at a tertiary care hospital, Rawalpindi. The study duration was 6 months from February 2021 until July 2021. The sample size was calculated to be 88. The intervention group was given a diet-related mobile app, and the usual care group was handed a pamphlet with diet instructions on discharge. Results The mean weight of all participants was 15 (SD 5.7) kg at the time of discharge. However, at the end of the 8th week, the mean weight of the participants in the usual care group was 16.5 (SD 7.2) kg and that of the intervention group was 17.1 (SD 5) kg. The average calories consumed by the usual care group was 972 (SD 252) kcal and 1000.75 (SD 210) kcal by the intervention group after 8 weeks of discharge. The average proteins consumed by the usual care group was 34.3 (SD 12.5) grams and 39 (SD 6.4) grams by the intervention group after 8 weeks of discharge. At the end of the intervention, the preferred diet planning tool for 79% of the participants was mobile app. At the 8th week, 93% of the participants considered the visual cues useful, 80% thought that the mobile app’s language was understandable, 79% thought nutritional goal setting is a useful feature in the mobile app, and 55% thought the recipes provided in the app were useful. Conclusions This study showed strength for the future of scalable modern technology for self-nutrition monitoring. There was a slight increase in the weight and nutritional intake of both groups, as the intervention period was limited. Trial Registration ClinicalTrials.gov NCT04782635; https://www.clinicaltrials.gov/ct2/show/NCT04782635

Emerging From Behind the Workstation.

Emerging From Behind the Workstation.

Analysis of the change of artificial intelligence to online consumption patterns and consumption concepts

In order to explore the change of artificial intelligence to online consumption patterns and consumption concepts, this paper explores the changes of artificial intelligence to online consumption patterns and consumption concepts, which are mainly realized through intelligent platforms. Moreover, this paper uses intelligent algorithms to improve the efficiency of system processing data, and uses data mining algorithms to process consumption patterns and consumption concept data. In addition, this paper studies the size and effect of the intermediary role played by payment mental accounts in payment costs and consumer purchase decisions, and studies the changes and effects of artificial intelligence on people's consumption patterns. Finally, this paper analyzes the changes of artificial intelligence to online consumption patterns and consumption concepts by investigating access methods and big data technology. Through investigation and research, we know that artificial intelligence can change consumption patterns, and make people more willing to accept this pattern of smart consumption, and it improves the convenience of people's consumption.

Effects of Artificial Intelligence in the Modern Business Client Artificial Intelligence Application and Audit Quality

Effects of Artificial Intelligence in the Modern Business Client Artificial Intelligence Application and Audit Quality