Predicting the conversion of minor cognitive impairment to dementia using default mode network and convolutional neural network
Principal Investigator: Professor Carola-Bibiane Schönlieb
Approved Research ID: 52802
Approval date: November 20th 2019
Age-related diseases pose significant challenges to our society. Dementia, one of the main causes of the disability and dependency of the ageing population, has a substantial impact on global economics. Mild cognitive impairment (MCI) is considered a transitional state between typical ageing and dementia. Early detection of the patient with MCI progressing into dementia is crucial. In this proposal, we plan to investigate whether neuroimaging integrated with deep learning algorithms could be useful to predict the conversion of MCI to dementia. The project duration is estimated to be 8 months. The results would provide a non-invasive early detection tool for the ageing group and thus would have crucial significance for public health management.