| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_8d0fc2b70675ee19bd5fc464f5ae9061 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-0059
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-7275
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-1455
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-7264
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N21-658
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B40-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B40-10 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N21-65
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B5-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B5-1455
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-20 |
| filingDate |
2020-01-13-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_e3592b264693f52318a0d2e8c31fcd7e
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_d7e68d114bee17bb3c17f02e4a9d938e
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_016bef594b18c9772beeaf4129db6e62
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_83bdc2fd032254c0ec554724446fb451 |
| publicationDate |
2021-07-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-113194820-A |
| titleOfInvention |
Method and system for providing cancer diagnosis information using liquid biopsy based on artificial intelligence with exosomes |
| abstract |
The artificial intelligence-based method for providing cancer diagnosis information using liquid biopsy by means of exosomes according to an embodiment of the present invention may include: the step of measuring the SERS (Surface Enhanced Raman Spectroscopy) signal of exosomes in cultured cells; The step of training a deep learning model by exosome SERS signal; the step of measuring blood exosome SERS signal; the step of analyzing the blood exosome SERS signal by the deep learning model trained with the cultured cell exosome SERS signal ; and the step of analyzing the similarity between the blood exosome data analyzed by the deep learning model and the cultured cell exosome data. |
| priorityDate |
2019-03-04-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |