骨闪烁照相术
接收机工作特性
计算机科学
决策支持系统
人工智能
人口
人工神经网络
放射科
医学
机器学习
环境卫生
作者
Mattias Ohlsson,Reza Kaboteh,May Sadik,Madis Suurküla,Milan Lomsky,Peter Gjertsson,Karl Sjöstrand,Jens Richter,Lars Edenbrandt
标识
DOI:10.1109/cbms.2009.5255270
摘要
A quantitative analysis of metastatic bone involvement can be an important prognostic indicator of survival or a tool in monitoring treatment response in patients with cancer. The purpose of this study was to develop a completely automated decision support system for whole-body bone scans using image analysis and artificial neural networks. The study population consisted of 795 whole-body bone scans. The decision support system first detects and classifies individual hotspots as being metastatic or not. A second prediction model then classifies the scan regarding metastatic disease on a patient level. The test set sensitivity and specificity was 95% and 64% respectively, corresponding to 95% area under the receiver operating characteristics curve.
科研通智能强力驱动
Strongly Powered by AbleSci AI