| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_e757fd4fedc4fe825bb81b1b466a0947 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F16-583
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-048
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F17-30598
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N5-02
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H30-40
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F16-285
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H30-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H70-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F16-51
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H10-60
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F17-3028 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N5-02
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H30-20 |
| filingDate |
2018-11-13-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_904d60aacee6b744c4fb8483aa15f367
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_642da5e59787e54a8eea1b0a023daece
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_bd9fcc4dd8f85597a55ecf3492ac3aec |
| publicationDate |
2019-12-05-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-2019370387-A1 |
| titleOfInvention |
Automatic Processing of Ambiguously Labeled Data |
| abstract |
A mechanism is provided that implements a cognitive data processing system for automatically processing ambiguously labeled data associated with a medical image. The cognitive data processing system receives an ambiguously labeled set of training data in which the ambiguously labeled set of training data comprises portions of data and associated labels, and wherein at least one portion of data in the ambiguously labeled set of training data has a plurality of different labels that together render the portion of data ambiguously labeled. The cognitive data processing system configures an implementation of a model that comprises a loss term, a maximizing term, and a sparsity term. The cognitive data processing system processes the ambiguously labeled set of training data based on the model to identifying a mapping that minimizes a loss function and thereby train the cognitive data processing system. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11531851-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2020303060-A1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2021406681-A1 |
| priorityDate |
2018-05-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |