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Subject: Artificial intelligenceWoS Q: Q2

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Now showing 1 - 2 of 2
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    Review
    Citation - WoS: 2
    Citation - Scopus: 2
    Artificial intelligence's impact on oral healthcare in terms of clinical outcomes: a bibliometric analysis
    (Emerald Group Publishing Ltd, 2024) AlQaifi, Faten; Tengilimoglu, Dilaver; Aras, Ilknur Arslan
    Purpose - This study provides a comprehensive overview of the impact of artificial intelligence (AI) applications on oral healthcare, focusing on clinical outcomes. Design/methodology/approach - A systematic approach was used to gather articles from databases such as Scopus, ScienceDirect, PubMed, Web of Science and Google Scholar from 2010 to 2024. The selection criteria included articles published in English, focusing solely on clinical applications of AI in dentistry. Articles such as conference proceedings, editorial material and personal opinions were excluded. The articles were analyzed and visualized using Rayyan software, Microsoft Excel and VOSviewer. Findings - Results indicate that 120 publications were authored by 58 scholars from 92 institutions across 29 countries, with a notable surge since 2018. This analysis showed the significant emphasis on the use of deep learning, demonstrating its high accuracy and performance in oral healthcare, often exceeding that of dentists. It also proved that even though AI is sometimes seen as an auxiliary tool, many studies revealed that AI has a performance near dental professionals' levels. Findings concluded that the majority of studies indicate that AI is generating better clinical outcomes in oral healthcare. Practical implications - This study provides dental professionals with insights on integrating AI for better diagnosis and treatment. Policymakers and healthcare institutions can use these findings to inform AI adoption and training strategies. Originality/value - It presents novel and valuable findings that can benefit various stakeholders by shedding light on the present scenario and potential future paths of AI integration in oral healthcare, contributing to its overall advancement.
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    Review
    Citation - WoS: 27
    Citation - Scopus: 45
    Impact of Nanotechnology on Conventional and Artificial Intelligence-Based Biosensing Strategies for the Detection of Viruses
    (Springer, 2023) Ramalingam, Murugan; Jaisankar, Abinaya; Cheng, Lijia; Krishnan, Sasirekha; Lan, Liang; Hassan, Anwarul; Marrazza, Giovanna
    Recent years have witnessed the emergence of several viruses and other pathogens. Some of these infectious diseases have spread globally, resulting in pandemics. Although biosensors of various types have been utilized for virus detection, their limited sensitivity remains an issue. Therefore, the development of better diagnostic tools that facilitate the more efficient detection of viruses and other pathogens has become important. Nanotechnology has been recognized as a powerful tool for the detection of viruses, and it is expected to change the landscape of virus detection and analysis. Recently, nanomaterials have gained enormous attention for their value in improving biosensor performance owing to their high surface-to-volume ratio and quantum size effects. This article reviews the impact of nanotechnology on the design, development, and performance of sensors for the detection of viruses. Special attention has been paid to nanoscale materials, various types of nanobiosensors, the internet of medical things, and artificial intelligence-based viral diagnostic techniques.