A Deep Learning Approach to Neuroanatomical Characterisation of Alzheimers Disease

摘要：

　　Alzheimers disease(AD)is a neurological degenerative disorder that leads to progressive mental deterioration.This work introduces a computational approach to improve our understanding of the progression of AD.We use ensemble learning methods and deep neural networks to identify salient structural correlations among brain regions that degenerate together in AD; this provides an understanding of how AD progresses in the brain.The proposed technique has a classification accuracy of 81.79%for AD against healthy subjects using a single modality imaging dataset.

关键词： Alzheimer Disease Machine Learning Artificial Intelligence

作者: Abhinit Kumar Ambastha Tze-Yun Leong

作者单位: Medical Computing Laboratory,School of Computing,National University of Singapore,Singapore Medical Computing Laboratory,School of Computing,National University of Singapore,Singapore;School o

会议类型: 国际会议

会议名称: 第十六届世界医药健康信息学大会((MEDINFO2017)、第二届世界医药健康信息学华语论坛(WCHIS 2017)、第15届全国医药信息学大会(CMIA 2017)

会议地点: 苏州

会议语种:英文

页码: 1249-1249

在线出版日期: 2017-08-21（万方平台首次上网日期，不代表论文的发表时间）