机器学习在急诊医学中应用的研究进展及展望

随着信息技术及医疗数据信息化的不断发展,越来越多的临床医生认识到人工智能或将彻底改变医学实践。机器学习可对大量医疗数据进行学习,探索数据集中的依赖关系,从而形成相应的医学模型;模型可对新的数据进行快速准确预测,有利于疾病早期诊断分级、辅助制定临床决策等。急诊医学面临着医疗资源相对短缺、急危重症患者识别及快速诊治需求等现状。在大数据时代,以临床需求为导向,机器学习为手段的智慧医疗或将成为解决上述问题的关键之一。

Development and prospect of the application of machine learning in emergency medicine

With the continuous development of information technology and medical data informatization,more and more clinicians realize that artificial intelligence may completely change medical practice. Machine can learn from a large amount of medical data,explore the dependencies of the data set,and form a corresponding medical model;the model can quickly and accurately predict new data,which is conducive to early disease diagnosis and classification,and assists in making clinical decisions. Emergency medicine is facing the relative shortage of medical resources,the identification of critically ill patients and the need for prompt diagnosis and treatment. In the era of big data,smart medical care based on clinical need and machine learning may become one of the keys to solving the above problems.