Predicate |
Object |
assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_57f3e2af72b2933c004ed61dfccaaee1 |
classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N2800-52 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-11 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N2800-54 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10056 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30024 |
classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0012 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N33-57415 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-12 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V20-698 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V10-7796 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06K9-00147 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2193 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06K9-6265 |
classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-11 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-12 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N33-574 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-00 |
filingDate |
2017-06-02-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
grantDate |
2022-02-22-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_dbc9633fd8f2e9ef214babbbf7292c3f http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9e27ee82b49839546a3f60ffb633b931 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_c4f550c62b7a8a776ef37546273411b4 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_05570762629e51b58e4479b61fbebe76 |
publicationDate |
2022-02-22-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
publicationNumber |
US-11257209-B2 |
titleOfInvention |
Cancer risk stratification based on histopathological tissue slide analysis |
abstract |
The subject disclosure presents systems and computer-implemented methods for providing reliable risk stratification for early-stage cancer patients by predicting a recurrence risk of the patient and to categorize the patient into a high or low risk group. A series of slides depicting serial sections of cancerous tissue are automatically analyzed by a digital pathology system, a score for the sections is calculated, and a Cox proportional hazards regression model is used to stratify the patient into a low or high risk group. The Cox proportional hazards regression model may be used to determine a whole-slide scoring algorithm based on training data comprising survival data for a plurality of patients and their respective tissue sections. The coefficients may differ based on different types of image analysis operations applied to either whole-tumor regions or specified regions within a slide. |
isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2021407076-A1 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11681418-B2 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11675178-B2 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2021027890-A1 |
priorityDate |
2014-12-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
type |
http://data.epo.org/linked-data/def/patent/Publication |