http://rdf.ncbi.nlm.nih.gov/pubchem/patent/KR-20200143157-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_cc88e78af0e5df147d5b2329384a7dc4 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-004 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B20-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H10-20 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B20-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H10-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-00 |
| filingDate | 2019-06-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_848f28b1f9d16290dec4cc4dc3f73718 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_8a44021748f0e9fc42422a8fea95296a http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_49f696ad7fed897480b128ae62637bd5 |
| publicationDate | 2020-12-23-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | KR-20200143157-A |
| titleOfInvention | Apparatus and system for prescribing personal-ustomized drugs or nutraceuticals using artificial intelligence |
| abstract | Provides a method for prescribing patient-tailored drugs using artificial intelligence at the start of the day, and the method periodically acquires medical data including gene expression distribution of patients who have received drugs prepared to treat the first disease. The step of, determining a second disease that may be onset to the patient from the gene expression distribution of the patient who has been treated for the first disease, receiving the patient's biometric information from the patient's terminal, and determining the patient's biometric information based on the patient's biometric information. 2 The second disease corresponding to the current patient's condition using the first artificial intelligence learning model that has learned the relationship between the second disease prevention method according to the step of determining the likelihood of a disease and the number of the second disease Generating preventive information of, reflecting the past health status, current health status, and future health status over time and creating the second disease prevention information by expressing the patient's character, prevention information of the second disease It may include the step of providing the patient's character reflected in the patient's terminal. |
| isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/KR-102505980-B1 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2022158615-A1 |
| priorityDate | 2019-06-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 189.