机器学习在肝脏疾病诊疗中的应用进展

Advances in machine learning in treatment and diagnosis of liver disease

目的总结机器学习在肝脏疾病诊疗中的应用进展。方法复习近年来有关机器学习在肝脏疾病的诊断、治疗、预后方面研究进展的相关文献并加以综述。结果机器学习有助于对肝实质性病变、肿瘤性病变以及少见肝脏疾病进行早期诊断和分类,有利于临床医师尽早采取对应的治疗措施;有助于为临床医师选择最佳治疗决策提供参考,有利于降低医疗风险;有助于综合判断患者的预后情况,为患者制定早期康复治疗计划、调整随访策略、改善未来预后等多方面提供帮助。结论通过多种机器学习算法构建的不同的预测模型,在肝脏疾病领域的临床应用中取得了良好的效果,并且在肝脏疾病的诊断、治疗、预后等多方面存在着较大潜力和良好前景。

Objective To summarize advances in the application of machine learning in the diagnosis and treatment of liver disease.Method The recent literatures on the progress of machine learning in the diagnosis,treatment and prognosis of liver diseases were reviewed.Results Machine learning could be used to diagnose and categorize substantial liver lesions,tumourous lesions and rare liver diseases at an early stage,which could facilitate clinicians to take timely and appropriate treatment measures.Machine learning was helpful in informing clinicians in choosing the best treatment decision,which was conducive to reducing medical risks.It could also help to determine the prognosis of patients in a comprehensive manner,and provide assistance in formulating early rehabilitation treatment plans,adjusting follow-up strategies and improving future prognosis.Conclusions Multiple types of machine learning algorithms have achieved positive results in the clinical application of liver diseases by constructing different prediction models,and have great potential and excellent prospects in multiple aspects such as diagnosis,treatment and prognosis of liver diseases.