人工智能多模块融合辅助早期尘肺病诊断的设想  

Multi-module fusion application of artificial intelligence in early pneumoconiosis screening

作　　者：佘权 吴雨晨[1] 徐酩[1] 韩磊[1] 王福如[1] SHE Quan;WU Yuchen;XU Ming;HAN Lei;WANG Furu(Jiangsu Provincial Center for Disease Control and Prevention,Hospital Public Health management Office,Nanjing,Jiangsu210009,China)

机构地区：[1]江苏省疾病预防控制中心医院公共卫生管理办公室,江苏南京210009

出　　处：《工业卫生与职业病》2025年第2期171-176,共6页Industrial Health and Occupational Diseases

基　　金：医防结合体制机制研究(M2022085);江苏省科技计划专项资金(重点研发计划社会发展)项目(BE2022803)。

摘　　要：尘肺病危害严重且常见,开展尘肺早期诊断至关重要。近年来,以人工智能(atrificial intelligence,AI)为代表的计算机科学和以组学为代表的高通量测序技术在医疗领域中占据重要地位。然而,AI在获取数据的质量、多样性、可解释性以及伦理问题方面面临着一定的挑战和机遇。将AI与临床组学及生物信息组学结合应用能够显著提升尘肺早期诊断的准确性。本文从尘肺早期诊断的意义、人工智能技术概况及在AI辅助诊断的多模块融合应用的研究现状等方面进行综述,为尘肺病早诊断早治疗提供参考。Pneumoconiosis is a severe and common disease.Early diagnosis of pneumoconiosis is essential.In recent years,computer science,represented by artificial intelligence(AI),and high-throughput sequencing technology,represented by omics,have played a significant role in the medical field.However,AI faces particular challenges and opportunities regarding data quality,diversity,interpretability,and ethical issues.Combining AI with clinical omics and bioinformatics can significantly improve the accuracy of pneumoconiosis screening.This article reviews the significance of pneumoconiosis screening,the overview of artificial intelligence technology,and the current research status of multi-module fusion applications in pneumoconiosis screening.

关 键 词：尘肺 人工智能 早期诊断 预测模型 多组学 

分 类 号：R135[医药卫生—劳动卫生]