http://rdf.ncbi.nlm.nih.gov/pubchem/patent/EP-3384856-A1

Outgoing Links

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assignee http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_8d1628ddb4cf617468e545f193da93df
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0012
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V20-698
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H40-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-10
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F19-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B10-02
filingDate 2016-10-11-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9aaa16984288754f7a036c3844dbb391
publicationDate 2018-10-10-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber EP-3384856-A1
titleOfInvention Cell abnormality diagnosing system using dnn learning, and diagnosis managing method of same
abstract The present invention is a technology relating to cell abnormality diagnosis system using DNN learning, which comprises a cell diagnosis device being installed in a each hospital and determining normal cells or dangerous cells on the basis of neural network as to inspection-subject cell photos; and a neural network learning server being connected to the Internet and performing DNN learning on the neural network of the cell diagnosis device. In particular, the present invention relates to a technology in which inspection-subject cell photos and diagnostic result data are acquired in each hospital and then uploaded to the neural network learning server, and then on the basis of this information the learning server performs DNN learning on a neural network model which is installed in the cell diagnosis device of the hospital so as to generate an upgrade neural network model as well as to download the same to the cell diagnosis device, so that cell diagnosis device becomes to form a neural network model which is optimized to the diagnosis environment of the hospital.
priorityDate 2015-11-30-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

Incoming Links

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Total number of triples: 20.