http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2005117707-A2

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assignee http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_e383ee71d45e93f2e090abd44dfc3744
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_812dc112784d8b5ba818811352a8da95
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-00
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B6-00
filingDate 2005-06-02-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_eede2562ac5297d9ce2bb5d4df74155d
publicationDate 2005-12-15-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber WO-2005117707-A2
titleOfInvention Automated detection of alzheimer's disease by statistical analysis with positron emission tomography images
abstract A method for detecting Alzheimer's disease using positron emission tomography. A normal population mean is obtained using PET. The normal population mean is obtained through the assimilation of a number of normal brain scans. Non-AD images and AD images are compared to observe differences in the uptake of FDG. PET scan results are expressed as relative uptake intensities and indexed by Brodmann's areas. An image is tested by comparing the distance of each mean for each Brodmann's area from the normal distribution. A Receiver Operating Characteristic curve is plotted based on the variation of deviation for the total population of both normal and probable Alzheimer's brain images. Variations in FDG uptake in a brain image as compared to the normal distribution confirms the probability of AD.
isCitedBy http://rdf.ncbi.nlm.nih.gov/pubchem/patent/JP-2010517030-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/JP-2010520478-A
priorityDate 2004-06-02-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

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isDiscussedBy http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID53716604
http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID226399674

Total number of triples: 16.