【摘 要】
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Functional networks are extracted from resting state functional magnetic resonance imaging data to explore biomarkers for distinguishing brain disorder in disease diagnosis.Previous works have primari
【出 处】
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第二届中国计算机学会生物信息学会议
论文部分内容阅读
Functional networks are extracted from resting state functional magnetic resonance imaging data to explore biomarkers for distinguishing brain disorder in disease diagnosis.Previous works have primarily focused on using a single resting state network(RSN)with various techniques.Here,we apply fusion analysis of RSNs to capturing biomarkers,which can combine the complementary information among the RSNs.Experiments are carried out on three groups of subjects,i.e.,cognition normal,early mild cognitive impairment and Alzheimers disease(AD),which correspond to the three progressing stages of Alzheimers disease,and each contains 18 subjects.
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