http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113222915-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30016 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-006 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-33 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V10-40 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0012 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-11 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V10-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-241 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-40 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-764 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-774 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-11 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-33 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-00 |
| filingDate | 2021-04-28-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2022-09-23-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2022-09-23-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-113222915-B |
| titleOfInvention | A method for establishing a PD diagnostic model based on multimodal magnetic resonance imaging |
| abstract | The invention discloses a method for establishing a PD diagnosis model based on multimodal magnetic resonance imaging omics. The diagnostic model constructed by learning is expected to improve the current situation that PD diagnosis is overly dependent on subjective assessment. Through image processing, data segmentation, feature extraction, feature screening, model construction and external independent verification, the present invention obtains a group of brain imaging features mainly based on the distribution of substantia nigra iron, and also has better external independent verification. diagnostic accuracy. Secondly, the random forest classifier constructed based on the above-mentioned brain radiomics features was used in diagnosing PD in different clinical states (early, middle-advanced patients and PD patients without drug treatment and drug treatment, tremor-predominant PD and non-tremor as patients with predominant PD) performed well. |
| priorityDate | 2021-04-28-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 41.