首页|在老年女性中以人工智能+云诊断细胞学阅片为主导的宫颈癌联合筛查模式应用分析

在老年女性中以人工智能+云诊断细胞学阅片为主导的宫颈癌联合筛查模式应用分析

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目的 探讨在老年女性中基于人工智能+云诊断细胞学阅片为主导的联合宫颈癌筛查模式的应用效果及价值。方法 回顾性分析2017年1月至2021年12月连云港市妇幼保健院行宫颈锥切治疗的319例宫颈上皮内瘤变(CIN)患者病历资料,其中传统细胞学检查联合人乳头瘤病毒(HPV)检测84例作为A组,人工智能+云诊断细胞学阅片联合HPV检测127例作为B组,人工智能+云诊断细胞学阅片联合高危HPV E6/E7 mRNA检测108例作为C组,比较各组年龄、孕次、阴道镜活检点数、绝经率、转化区完全可见率、宫颈管搔刮率、治疗间隔时间、冷刀锥切率、锥切后病变一致率、锥切后病变升级率。结果 各组之间年龄、孕次、阴道镜活检点数、绝经率、转化区完全可见率、宫颈管搔刮率、治疗间隔时间、冷刀锥切率等指标比较,差异无统计学意义(P>0。05)。B组和C组锥切后病理结果的一致率高于A组,病变升级率低于A组,差异有统计学意义(P<0。05)。结论 在老年女性中,基于人工智能+云诊断细胞学阅片技术的宫颈癌联合筛查模式具有更低的漏诊率和更高的准确率,更适用于老年女性宫颈癌筛查。
Application analysis of the cervical cancer combined screening model dominated by artificial intelligence and cloud diagnostic cytology screen-ing in elderly women
Objective To explore the application effect and value of the cervical cancer combined screening model domi-nated by artificial intelligence+cloud diagnostic cytology screening in elderly women.Methods The medical records of 319 patients with cervical intraepithelial neoplasia(CIN)who underwent cervical conization treatment at Lianyungang Maternal and Child Health Hospital from January 2017 to December 2021 were retrospectively analyzed.Among them,84 cases were treated with traditional cytology combined with human papilloma viru(HPV)detection as group A,127 cases were treated with artificial intelligence+cloud diagnostic cytology screening combined with HPV detection as group B,and 108 cases were treated with artificial intelligence+cloud diagnostic cytology screening combined with high-risk HPV E6/E7 mRNA detec-tion as group C.The age,gestational age,number of vaginal biopsy sites,menopausal rate,complete visualization rate of transition zone,cervical scraping rate,treatment interval time,cold knife conization rate,post conization lesion consistency rate,and post conization lesion escalation rate among three gropes were compared.Results There were no statistically sig-nificant difference in age,gestational age,number of vaginal biopsy sites,menopausal rate,complete visualization rate of transition zone,cervical scraping rate,treatment interval time,and cold knife conization rate among each group(P>0.05).The consistency rate of pathological results after conization in group B and group C was higher than that in Group A,and the disease escalation rate was lower than that in group A,the differences were statistically significant(P<0.05).Conclusion Among elderly women,the cervical cancer combined screening model based on artificial intelligence and cloud diagnosis cytology screening have a lower missed diagnosis rate and higher accuracy,making it more suitable for screening cervical cancer in elderly women.

Artificial intelligenceCloud diagnosticsCervical cancer screeningColposcopyCervical conization

姚军、张丽姣、李建伟、周哲

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江苏省连云港市妇幼保健院妇科,江苏连云港 222000

人工智能 云诊断 宫颈癌筛查 阴道镜检查 宫颈锥切

江苏省连云港市老龄健康科研项目

L202210

2024

中国当代医药
中国保健协会 当代创新(北京)医药科学研究院

中国当代医药

影响因子:1.215
ISSN:1674-4721
年,卷(期):2024.31(5)
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