| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_f987b6a5eb232de4e7d6e9d5ddd0d7e4 |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2200-24
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-088
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2219-004 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F40-30
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H10-60
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-30
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F40-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F40-295
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T19-00 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H10-60 |
| filingDate |
2018-11-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_1c63c41fdfb63d2d5874ef204643c179
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f52f85193d9c7450c0e55a96d5797eb5
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_a2693f056d99cf556b394c12390c675d
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_de26e673cb735da94945c577bd06b806
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_2bf0beb7c6bdda1da3df3541ff615c81
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_60de7d0c9f618a901f482a1816a8ecff
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_51b5419dcea4b9f01c346b2d2016ef82 |
| publicationDate |
2020-01-23-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-2020027531-A1 |
| titleOfInvention |
Digital representations of past, current, and future health using vectors |
| abstract |
A computing entity accesses instances of medical information corresponding to a population of patients and generates a plurality of medical sentences corresponding to the population by, for each patient of the population, generating one medical sentence corresponding to the patient and a timestamp associated with each instance such that the one medical sentence comprises one or more medical codes in a chronological order. The computing entity generates a vector dictionary comprising a plurality of multi-dimensional vectors based on a vector generation model trained using machine learning and the plurality of medical sentences with each multi-dimensional vector corresponding to a medical code. The computing entity generates a digital representation of a first patient of the population using an anagram model and the vector dictionary, determines a health state of the first patient based on the digital representation, and provides an output indicating the health state of the first patient. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11790638-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11257592-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11288494-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2022067004-A1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11763547-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114864088-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11763548-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2021090745-A1 |
| priorityDate |
2018-07-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |