A Just-in-Time Learning Based Monitoring and Classification Method for Hyper/Hypocalcemia Diagnosis

作者：Peng, Xin^*; Tang, Yang; He, Wangli; Du, Wenli; Qian, Feng

来源：IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018, 15(3): 788-801.

DOI：10.1109/TCBB.2017.2655522

• Calcium regulation
• calcium-related pathologies
• feature extraction
• Just-in-Time modeling
• mixture models
• non-Gaussian process
• online modeling
• performance monitoring

This study focuses on the classification and pathological status monitoring of hyper/hypo-calcemia in the calciumregulatory system. By utilizing the Independent Component Analysis (ICA) mixture model, samples from healthy patients are collected, diagnosed, and subsequently classified according to their underlying behaviors, characteristics, and mechanisms. Then, a Just-in-Time Learning (JITL) has been employed in order to estimate the diseased status dynamically. In terms of JITL, for the purpose of the construction of an appropriate similarity index to identify relevant datasets, a novel similarity index based on the ICA mixture model is proposed in this paper to improve online model quality. The validity and effectiveness of the proposed approach have been demonstrated by applying it to the calciumregulatory systemunder various hypocalcemic and hypercalcemic diseased conditions.

• 出版日期2018-6
• 单位华东理工大学