Creatinine Prediction From Body Composition A Neural Network Approach

摘要：

Creatinine,a naturally-produced chemical compound in blood,has been commonly used as a reliable indicator of kidney function. Creatinine level is typically obtained from blood-test.In this paper, a technique for predicting the criticality of creatinine level in blood is presented.The proposed technique takes only body size and mass parameters obtained from advanced weighing scale and body scanner, allowing the prediction to be done more casually.The technique applies a multi-layered feed-forward neural network for developing the prediction model.The achieved overall prediction accuracy is in the vicinity of 88％ where the average false negative rate and the average false positive rate are 22.15％ and 8.26％, respectively.

关键词： Neural Network Creatinine Prediction Kidney Health

作者: Thitipong Tanprasert Chularat Tanprasert

作者单位: Department of Computer Science Faculty of Science and Technology Assumption University Bangkok,THAIL Knowledge Elicitation and Archiving Laboratory National Electronics and Computer Technology Center N

会议类型: 国际会议

会议名称: The 10th International Conference on Intelligent Technologies(第十届智慧科技国际会议 InTech09)

会议地点: 桂林

会议语种:英文

页码: 49-52

在线出版日期: 2009-12-12（万方平台首次上网日期，不代表论文的发表时间）