人工智能在检验医学应用研发中的问题剖析及应对策略

Problems and countermeasures in the application of artificial intelligence in laboratory medicine research and development

人工智能在检验医学中的应用研究已经成为检验发展的重要方向,但人工智能技术在产品应用研发过程中仍存在机器学习模型缺乏可解释性、人才队伍缺乏、安全隐患众多等问题。其原因可能有数据集质量不高、研究设计偏差、人才培养机制不健全、立法和监管不到位等。针对这些形成原因,可以采取相应对策,包括建立数据录入和采集规范,制定数据标注管理标准、做好模型的风险分析,加强复合型人才培养,健全监督管理体系等。确保检验医学领域应用的人工智能产品能够在提升诊断效率、减少误诊和漏诊率的前提下,切实提升医疗服务质量。

Research on the application of artificial intelligence in laboratory medicine has become an important direction for laboratory development.However,there were still problems in the process of product application research and development of artificial intelligence technology,such as lack of interpretability of machine learning models,lack of talent teams,and many potential safety hazards.The reason for this may include low quality of data sets,deviations in research design,imperfect talent training mechanism,and inadequate legislation and supervision.In response to these reasons,the article proposes countermeasures,including establishing data entry and collection standards,formulating data labeling management standards,making model risk analysis,strengthening compound talent training,and improving supervision and management systems.Ensuring artificial intelligence products applied in the field of laboratory medicine could effectively improve the quality of medical services on the premise of improving the efficiency of diagnosis and reducing the rate of misdiagnosis and missed diagnosis.