人工智能在临床牙科中的应用,文献综述。

Kimia Ghods, Arash Azizi, Aryan Jafari, Kian Ghods
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引用次数: 0

摘要

问题简介:近年来,人工智能(AI)在牙科领域的应用日益普及,因为它能为诊断和临床决策过程提供便利。然而,人工智能存在多个突出缺点,限制了其在当今的广泛应用。目的:因此,本研究全面回顾了人工智能在所有牙科领域的各种应用及其优缺点:为了撰写这篇综述文章,我们在 PubMed 和 Google Scholar 数据库中进行了全面查询,并使用关键词 "人工智能"、"牙科"、"机器学习"、"深度学习 "和 "诊断系统 "收集了 2010-2022 年间发表的研究。最终,116 篇以人工智能在牙科领域的应用为主题的相关文章被选中并进行了评估:在新的研究中,人工智能在以下方面的应用被提及:根据放射学视图和组织病理学特征检测牙科异常和口腔恶性肿瘤、设计牙科种植体和牙冠、确定牙体预备完成线、分析生长模式、估算生物年龄、预测牙髓干细胞的活力、分析根尖周病变的基因表达、法医牙科以及预测治疗的成功率。尽管人工智能在临床牙科中大有裨益,但仍存在三个有争议的挑战,包括使用的便捷性、投资的经济回报和性能的证据,需要加以解决:从获得的结果来看,人工智能最关键的进步是在口腔恶性肿瘤的诊断系统中。然而,人工智能在牙科各分支领域的最新进展还需要进一步的科学研究才能应用于临床实践。此外,只有妥善应对人工智能面临的挑战,才能将其广泛应用于临床口腔医学。
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Application of Artificial Intelligence in Clinical Dentistry, a Comprehensive Review of Literature.

Statement of the problem: In recent years, the use of artificial intelligence (AI) has become increasingly popular in dentistry because it facilitates the process of diagnosis and clinical decision-making. However, AI holds multiple prominent drawbacks, which restrict its wide application today. It is necessary for dentists to be aware of AI's pros and cons before its implementation.

Purpose: Therefore, the present study was conducted to comprehensively review various applications of AI in all dental branches along with its advantages and disadvantages.

Materials and method: For this review article, a complete query was carried out on PubMed and Google Scholar databases and the studies published during 2010-2022 were collected using the keywords "Artificial Intelligence", "Dentistry," "Machine learning," "Deep learning," and "Diagnostic System." Ultimately, 116 relevant articles focused on artificial intelligence in dentistry were selected and evaluated.

Results: In new research AI applications in detecting dental abnormalities and oral malignancies based on radiographic view and histopathological features, designing dental implants and crowns, determining tooth preparation finishing line, analyzing growth patterns, estimating biological age, predicting the viability of dental pulp stem cells, analyzing the gene expression of periapical lesions, forensic dentistry, and predicting the success rate of treatments, have been mentioned. Despite AI's benefits in clinical dentistry, three controversial challenges including ease of use, financial return on investment, and evidence of performance exist and need to be managed.

Conclusion: As evidenced by the obtained results, the most crucial progression of AI is in oral malignancies' diagnostic systems. However, AI's newest advancements in various branches of dentistry require further scientific work before being applied to clinical practice. Moreover, the immense use of AI in clinical dentistry is only achievable when its challenges are appropriately managed.

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