Predicate |
Object |
assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_5f90b10d8968389d412d7f056534146b |
classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-7475 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-7435 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-0004 |
classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-0004 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-4866 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-4848 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-7267 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-7275 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-7435 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H10-60 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H15-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-7475 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H40-67 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-70 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-1118 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-14532 |
classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-20 |
filingDate |
2020-05-29-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_27b527760f5c2f468d1de3b11d75d6a5 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_ce5e0a2ed39ae3d284f717ae338407b8 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7ec1d20d63010bda0803c87d4cadcf81 |
publicationDate |
2022-01-20-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
publicationNumber |
AU-2020283127-A1 |
titleOfInvention |
Systems for biomonitoring and blood glucose forecasting, and associated methods |
abstract |
Systems and methods for biomonitoring and personalized healthcare are disclosed herein. In some embodiments, a computer-implemented method for forecasting a blood glucose state of a patient is provided. The method comprises: receiving blood glucose data of the patient; generating at least one initial prediction of the blood glucose state by inputting the blood glucose data into a first set of machine learning models; determining a plurality of features at least partly from the at least one initial prediction; and generating a final prediction of the blood glucose state by inputting the plurality of features into a second set of machine learning models. |
priorityDate |
2019-05-31-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
type |
http://data.epo.org/linked-data/def/patent/Publication |