| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_a490020fd2580d5f04cbe4ea55b65c3f |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F2218-12
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V10-82 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C12Q1-18 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/C12Q1-18 |
| filingDate |
2021-11-18-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_ada8e200cabd6e22b08363da8c786ad8 |
| publicationDate |
2022-05-27-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
WO-2022109091-A1 |
| titleOfInvention |
Antimicrobic susceptibility testing using recurrent neural networks |
| abstract |
An optimized testing method is used to determine minimum inhibitory concentration (MIC) of a particular antimicrobic for use on a sample. This may include iteratively imaging wells inoculated with the sample and containing various concentrations of the antimicrobic. The images are thereafter processed to identify MIC based on sequences in information provided as input to a machine learning model. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2023034046-A1 |
| priorityDate |
2020-11-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |