Study on the interaction between big data and artificial intelligence

Li, Jin; Ye, Zi‐Wei; Zhang, Caiming

doi:10.1002/sres.2878

Cited by 14 publications

(5 citation statements)

References 29 publications

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“…The accuracy of the steps directly affects the quality of the constructed map. Named entity recognition has many technical means [24]. In this paper, the main structural data sources for entity extraction are supported, and the extraction is carried out utilizing regularization, which realizes the data support for the expected functions, as shown in Figure 1.…”

Section: Convolution Neural Network-based Data Fusionmentioning

confidence: 99%

A Big Data-Driven Financial Auditing Method Using Convolution Neural Network

Zhao¹,

Wang

2023

IEEE Access

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In the big data era, traditional auditing methods are facing challenge such as limited audit scope, uneven distribution of audit power, and insufficient audit analysis. To pursue high efficiency, the utilization of big data analysis technique in financial auditing has been a novel tendency in this area. The deep learning has been popular in many areas due to its high freedom degree. Thus, this paper employs a typical deep learning model convolution neural network (CNN), and proposes a big data-driven financial auditing method using CNN. Specifically, the strong ability of feature abstraction of CNN is leveraged to extract multi-level features in materials, such as visual features, textual features, etc. Then, the multi-source features from auditing materials can be well fused for final discrimination. Some simulation experiments are conducted on real-world financial auditing scenes for assessment. And the results show that the designed the proposed financial auditing method possesses relatively high auditing accuracy.

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Section: Convolution Neural Network-based Data Fusionmentioning

confidence: 99%

A Big Data-Driven Financial Auditing Method Using Convolution Neural Network

Zhao¹,

Wang

2023

IEEE Access

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“…Limiting pre-operative difficulties, lowering hospital issues, and promoting recovery are some of the benefits of AI in the surgical sector. it can also be said that a smartphone device can help in decision-making while providing all with fact-based and practical outcomes, facilitating the best surgical outcomes which are cooperative and adaptable as per the patient's requests [99].…”

Section: ) Connectivity Equipmentmentioning

confidence: 99%

Toward IoRT Collaborative Digital Twin Technology Enabled Future Surgical Sector: Technical Innovations, Opportunities and Challenges

et al. 2022

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In today's world, it is anticipated that DTw and IoRT will transform the idea of digital healthcare and advancement of it what was previously unknown. DTw is (physical or virtual) machines or computer-based models capable of mimicking or "twinning" the lives of actual entities such as objects, humans, or human-related features. Since the advent of digital and smart healthcare, the world has swiftly integrated several technologies in healthcare to support improved patient service, extend life expectancy, and lower healthcare expenses.DTw and IoRT are promising technologies and great improvements in this field. In recent years, the concepts of IoRT and DTw have captured the interest of the surgical sector. The flawless integration of data between a physical and virtual machine in either direction is the best way to conduct smart surgery. Artificial intelligence, nanotechnology, various kinds of robotic equipment, and the Internet of Things (IoT) are our pillars of completing the task. Using the DTw technological framework and IoRT infrastructure, this review paper proposes a comparative overview of traditional and IoRT collaborated DTwT and executes an adaptive perspective, opportunities, and challenges in the healthcare sector, namely surgical advances. This is an important addition to digital surgeries and to improve healthcare operations. Our literature review has sorted them according to research areas: the technological innovation, the prospective and opportunities we have, problems facing the surgical industry today and in the future, and offers an evaluation of the enabling technologies for the betterment of employing DTw and IoRT for the developing and secure surgical sector for both patients and doctors.INDEX TERMS Digital twin technology (DTwT), Internet of Robotic things (IoRT), surgery, Future surgical sector, Healthcare,

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“…With the continuous development of financial markets and technological advancements, financial fraud has shown diverse and covert characteristics. Traditional manual detection methods can no longer meet the needs of real-time, efficient, and accurate fraud detection [1][2][3]. Traditional financial fraud detection methods mainly rely on rule engines and manual auditing.…”

Section: Introductionmentioning

confidence: 99%

Research on the Application of Artificial Intelligence and Big Data Technology in Financial Fraud Detection

Wang

2024

JTPES

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Financial fraud is a hidden criminal activity that has a serious impact on the stability of financial markets and investor confidence. Traditional fraud detection methods are often inefficient and unable to meet the rapidly changing fraudulent means. The development of artificial intelligence and big data technology has provided new solutions for financial fraud detection. This article aims to explore the current application status and methods of artificial intelligence and big data technology in financial fraud detection, and analyze the challenges and future development directions.

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Study on the interaction between big data and artificial intelligence

Cited by 14 publications

References 29 publications

A Big Data-Driven Financial Auditing Method Using Convolution Neural Network

A Big Data-Driven Financial Auditing Method Using Convolution Neural Network

Toward IoRT Collaborative Digital Twin Technology Enabled Future Surgical Sector: Technical Innovations, Opportunities and Challenges

Research on the Application of Artificial Intelligence and Big Data Technology in Financial Fraud Detection

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