Giovane Richard, Sheppard Robert A
Family Medicine, University of Alabama at Birmingham, Tuscaloosa, USA.
Internal Medicine, University of Alabama at Birmingham, Tuscaloosa, USA.
Cureus. 2022 Aug 31;14(8):e28635. doi: 10.7759/cureus.28635. eCollection 2022 Aug.
Bacteremia is a common and life-threatening condition. It has an incidence of 140 to 160 per 100,000 person-years in the United States. Since bacteremia has many presentations, it can be challenging to diagnose. Subsequently there are very few guidelines on when to order a blood culture in an emergency setting. Neural networks are a means of machine learning and are presently being used in medicine to aid in decision making. With the use of machine learning, 22 variables that have been associated with infection and bacteremia were used to build a neural network to determine which variables associated with bacteremia are most associated with a positive blood culture.
菌血症是一种常见且危及生命的病症。在美国，其发病率为每10万人年140至160例。由于菌血症有多种表现形式，诊断可能具有挑战性。随后，关于在紧急情况下何时进行血培养的指南非常少。神经网络是机器学习的一种手段，目前正在医学中用于辅助决策。通过使用机器学习，22个与感染和菌血症相关的变量被用于构建一个神经网络，以确定哪些与菌血症相关的变量与血培养阳性最相关。
