宫颈癌的高危因素和图像在人工智能构建预测模型中的应用与发展

Cervical Cancer Risk Factors of Imaging Application and Development Combined with Artificial Intelligence to Build a Prediction Model

摘要: 宫颈癌(CC)，作为女性中频发的致命肿瘤之一，其发病率位居乳腺癌之后。伴随社会经济条件的优化、生活品质的提高、医学知识的普及、女性对健康保护意识的增强以及医疗技术的不断发展，我国已经实施了针对宫颈病变的“三阶梯”筛查策略与“两癌”筛查项目的广泛推广，并且积极推动宫颈癌疫苗的普及工作。因此，国内宫颈癌的发展态势呈现出新的变化。最近，人工智能(AI)技术在妇科癌症诊疗领域的迅猛发展，展现了其在宫颈癌预测与诊断方面的有效性。通过运用AI预测模型，不仅提高了宫颈癌相关疾病诊断的精确度，减少了主观判断的误差，还有效降低了误诊率。帮助临床医生在实际工作中节省时间和精力，且有望解决我国医疗资源分布不均等问题。本文将结合国内外研究成果，从高危因素、细胞学检查、影像学检查三个方面出发，探讨AI预测模型在宫颈癌筛查和诊断中的应用，并提出未来AI在宫颈癌筛查和诊断中面临的挑战和进一步发展。

Abstract: Cervical cancer (CC), as one of the most frequent and fatal tumors in women, ranks second after breast cancer. With the optimization of social and economic conditions, the improvement of quality of life, the popularization of medical knowledge, the enhancement of women’s awareness of health protection and the continuous development of medical technology, China has implemented the “three-step” screening strategy for cervical lesions and the extensive promotion of the “two cancers” screening program, and actively promoted the popularization of cervical cancer vaccine. Therefore, the development trend of cervical cancer in China has shown new changes. Recently, the rapid development of artificial intelligence (AI) technology in the field of gynecological cancer diagnosis and treatment has demonstrated its effectiveness in the prediction and diagnosis of cervical cancer. The application of AI prediction model not only improves the accuracy of diagnosis of cervical cancer related diseases, reduces the error of subjective judgment, but also effectively reduces the misdiagnosis rate. It can help clinicians save time and energy in practical work, and is expected to solve the problem of unequal distribution of medical resources in China. Based on domestic and foreign research results, this paper will discuss the application of AI prediction model in cervical cancer screening and diagnosis from three aspects: high risk factors, cytology examination, imaging examination and propose future challenges and further development of AI in cervical cancer screening and diagnosis.