| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_c2fd875d0de1b231ba8ee4ea9c3dcd43
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_01d213f75765702302a15d513d25b85d |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61N2005-1041 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N5-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61N5-1038
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N7-01
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B6-032
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61N5-103
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61N5-1039
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N99-005
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N7-005 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N7-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N5-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B6-03
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61N5-10 |
| filingDate |
2018-07-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_8d0c1468d659a5e70e2543746dcae78f
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_a778deda98b1fb71e078312e3a4c4497 |
| publicationDate |
2018-11-01-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-2018311510-A1 |
| titleOfInvention |
System and method for automatic treatment planning |
| abstract |
The present disclosure relates to systems, methods, and computer-readable storage media for radiotherapy. Embodiments of the present disclosure may receive a plurality of training data and determine one or more predictive models based on the training data. The one or more predictive models may be determined based on at least one of a conditional probability density associated with a selected output characteristic given one or more selected input variables or a joint probability density. Embodiments of the present disclosure may also receive patient specific testing data. In addition, embodiments of the present disclosure may predict a probability density associated with a characteristic output based on the one or more predictive models and the patient specific testing data. Moreover, embodiments of the present disclosure may generate a new treatment plan based on the prediction and may use the new treatment plan to validate a previous treatment plan. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11494691-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-10332035-B1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2022261622-A3 |
| priorityDate |
2014-06-18-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |