Predicate |
Object |
assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_91623e18eded2311131906ba5797d8d7 |
classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N21-6458 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N21-6408 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10064 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30044 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10056 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 |
classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0012 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N21-6458 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H10-40 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-70 |
classificationIPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N21-64 |
classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-70 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-20 |
filingDate |
2022-04-04-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f3e36239a81876b37b1f006d7d8a1a25 |
publicationDate |
2022-10-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
publicationNumber |
WO-2022212950-A1 |
titleOfInvention |
Artificial intelligence methods for predicting embryo viability based on microscopy methods |
abstract |
Microscopy methods for determining embryo viability are described. A method can include accessing, at a compute device, fluorescence lifetime imaging microscopy (FLIM) data set associated with a biological material. The biological material can include either an embryo or a gamete. The method further includes extracting a fluorescence photon arrival time from a subset of data from the FLIM data set. The method further includes estimating a likelihood that the biological material will produce a successful pregnancy and/or a live birth based on the fluorescence photon arrival time histogram and an estimation model that has been trained using artificial intelligence and labeled clinical training data. The method includes generating an output signal representing the estimated likelihood that the biological material will produce a successful pregnancy and/or a live birth. In some embodiments, the method can include training the estimation model using a plurality of fluorescence photon arrival time histograms of the FLIM data set. |
priorityDate |
2021-04-02-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
type |
http://data.epo.org/linked-data/def/patent/Publication |