Diagnosis of Cervical Cancer and Pre-Cancerous Lesions by Artificial Intelligence: A Systematic Review.
Diagnosis of Cervical Cancer and Pre-Cancerous Lesions by Artificial Intelligence: A Systematic Review.
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DOI：
10.3390/diagnostics12112771
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发表时间：
2022-11-13
期刊：
影响因子：
3.6
通讯作者：
Alkatout, Ibrahim
中科院分区：
文献类型：
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作者：
Allahqoli, Leila;Lagana, Antonio Simone;Mazidimoradi, Afrooz;Salehiniya, Hamid;Guenther, Veronika;Chiantera, Vito;Goghari, Shirin Karimi;Ghiasvand, Mohammad Matin;Rahmani, Azam;Momenimovahed, Zohre;Alkatout, Ibrahim
目的：随着宫颈异常细胞的及时发现，宫颈癌得到及时治疗的可能性增大。由于手工鉴定需要熟练的病理学家，耗时且容易出错，因此建立了检测异常宫颈细胞的自动化方法。本系统综述的目的是评估人工智能（AI）技术在宫颈癌和癌前病变的预测、筛查和诊断方面的诊断性能。材料与方法：在Medline、Web of Science Core Collection（索引= SCI-EXPANDED、SSCI、a&hci Timespan）和Scopus三个数据库中进行综合检索，检索到2022年7月之前发表的论文。将人工智能技术应用于宫颈癌的预测、筛查和诊断的文章均被纳入本综述。没有时间限制。根据系统评价和荟萃分析指南的首选报告项目对文章进行检索、筛选、合并和分析。结果：初步检索得到2538篇文章。在筛选和评估合格性后，117项研究被纳入本综述。人工智能技术被发现在癌前和癌性宫颈病变的筛查系统中发挥着重要作用。这些算法预测宫颈癌的准确率从70%到100%不等。人工智能技术能够以80-100%的准确率区分癌变和正常的巴氏涂片。人工智能有望成为医生做出准确临床诊断的实用工具。AI在阴道镜下检测CIN2+的敏感性为71.9 ~ 98.22%，特异性为51.8 ~ 96.2%。结论：本综述强调了人工智能系统在宫颈癌和癌前病变的预测、筛查或检测方面的可接受性能，特别是在缺乏专业中心或医疗资源的情况下。与人类评估相结合，人工智能可以作为解释宫颈涂片或图像的有用工具。
Objective: The likelihood of timely treatment for cervical cancer increases with timely detection of abnormal cervical cells. Automated methods of detecting abnormal cervical cells were established because manual identification requires skilled pathologists and is time consuming and prone to error. The purpose of this systematic review is to evaluate the diagnostic performance of artificial intelligence (AI) technologies for the prediction, screening, and diagnosis of cervical cancer and pre-cancerous lesions. Materials and Methods: Comprehensive searches were performed on three databases: Medline, Web of Science Core Collection (Indexes = SCI-EXPANDED, SSCI, A & HCI Timespan) and Scopus to find papers published until July 2022. Articles that applied any AI technique for the prediction, screening, and diagnosis of cervical cancer were included in the review. No time restriction was applied. Articles were searched, screened, incorporated, and analyzed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Results: The primary search yielded 2538 articles. After screening and evaluation of eligibility, 117 studies were incorporated in the review. AI techniques were found to play a significant role in screening systems for pre-cancerous and cancerous cervical lesions. The accuracy of the algorithms in predicting cervical cancer varied from 70% to 100%. AI techniques make a distinction between cancerous and normal Pap smears with 80–100% accuracy. AI is expected to serve as a practical tool for doctors in making accurate clinical diagnoses. The reported sensitivity and specificity of AI in colposcopy for the detection of CIN2+ were 71.9–98.22% and 51.8–96.2%, respectively. Conclusion: The present review highlights the acceptable performance of AI systems in the prediction, screening, or detection of cervical cancer and pre-cancerous lesions, especially when faced with a paucity of specialized centers or medical resources. In combination with human evaluation, AI could serve as a helpful tool in the interpretation of cervical smears or images.
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DOI：
10.4274/jtgga.galenos.2020.2020.0119
发表时间：
2020-12-04
期刊：
Journal of the Turkish German Gynecological Association
影响因子：
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作者：
Alkatout I;Karimi-Zarchi M;Allahqoli L
通讯作者：
Allahqoli L
人工智能辅助细胞学诊断系统在大规模宫颈癌筛查中的应用：70万女性人群队列研究
影响因子：
4
作者：
Bao H;Sun X;Zhang Y;Pang B;Li H;Zhou L;Wu F;Cao D;Wang J;Turic B;Wang L
通讯作者：
Wang L
影响因子：
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作者：
Al-Batah, Mohammad Subhi;Isa, Nor Ashidi Mat;Al-Betar, Mohammed Azmi
通讯作者：
Al-Betar, Mohammed Azmi
影响因子：
1.8
作者：
Boon, ME;Ouwerkerk-Noordam, E;Kok, LP
通讯作者：
Kok, LP
DOI：
10.3390/s22114132
发表时间：
2022-05-29
期刊：
Sensors (Basel, Switzerland)
影响因子：
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作者：
通讯作者：
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