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IC‐P‐030: WORSENING FUNCTIONAL CONNECTIVITY WITHIN DEFAULT MODE NETWORK IS ASSOCIATED WITH HIGHER AV‐1451 PET UPTAKE IN MEDIAL TEMPORAL LOBE
Author(s) -
Scott David,
Bracoud Luc,
Adamczuk Kate,
Suhy Joyce
Publication year - 2019
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2019.06.4192
Subject(s) - default mode network , temporal lobe , functional connectivity , voxel , neuroscience , tau pathology , nuclear medicine , cardiology , resting state fmri , medicine , psychology , alzheimer's disease , disease , radiology , epilepsy
prediction (R 1⁄4 .75). Figure 2 depicts the error histogram for the test data for 1-5 year predictions. Most errors were clustered around zero, indicating little to no difference in the actual and predicted values. Conclusions: Machine learning algorithms can provide decision support and predictive analytics in medicine. Our model is highly accurate and capable of reliably forecasting changes in rsfc due to AD from 1-5 years in the future and illustrates the feasibility of applying machine learning algorithms for targeted patient care in AD individuals.