Ontology driven decision support for the diagnosis of mild cognitive impairment.
In recent years, mild cognitive impairment (MCI) has attracted significant attention as an indicator of high risk for Alzheimer's disease (AD), and the diagnosis of MCI can alert patient to carry out appropriate strategies to prevent AD. To avoid subjectivity in diagnosis, we propose an ontology driven decision support method which is an automated procedure for diagnosing MCI through magnetic resonance imaging (MRI). In this approach, we encode specialized MRI knowledge into an ontology and construct a rule set using machine learning algorithms. Then we apply these two parts in conjunction with reasoning engine to automatically distinguish MCI patients from normal controls (NC). The rule set is trained by MRI data of 187 MCI patients and 177 normal controls selected from Alzheimer's Disease Neuroimaging Initiative (ADNI) using C4.5 algorithm. By using a 10-fold cross validation, we prove that the performance of C4.5 with 80.2% sensitivity is better than other algorithms, such as support vector machine (SVM), Bayesian network (BN) and back propagation (BP) neural networks, and C4.5 is suitable for the construction of reasoning rules. Meanwhile, the evaluation results suggest that our approach would be useful to assist physicians efficiently in real clinical diagnosis for the disease of MCI.
School of Information Science and Engineering, Lanzhou University, Lanzhou, China.
Xiaowei
X
Zhang
College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China; School of Information Science and Engineering, Lanzhou University, Lanzhou, China; School of Computing, Telecommunications and Networks, Birmingham City University, UK. Electronic address: bh@lzu.edu.cn.
Bin
B
Hu
School of Information Science and Engineering, Lanzhou University, Lanzhou, China.
Xu
X
Ma
School of Computing, Telecommunications and Networks, Birmingham City University, UK.
Philip
P
Moore
School of Information Science and Engineering, Lanzhou University, Lanzhou, China.
Jing
J
Chen
D000465:Algorithms; D000544:Alzheimer Disease / Q000175:diagnosis; D001499:Bayes Theorem; D064229:Biological Ontologies; D001921:Brain / Q000473:pathology; D016022:Case-Control Studies; D060825:Cognitive Dysfunction / Q000175:diagnosis*; D019295:Computational Biology; D003661:Decision Support Techniques; D006801:Humans; D051188:Knowledge Bases; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data; D059906:Neuroimaging / Q000706:statistics & numerical data*
Alzheimer dementia; Decision tree; Diagnosis; Magnetic resonance imaging (MRI); Mild cognitive impairment; Ontology