US 12,402,837 B2
Tensor amplification-based data processing
Hendrikus Derksen, Dexter, MI (US); Neriman Tokcan, Somerville, MA (US); Kayvan Najarian, Northville, MI (US); and Jonathan Gryak, Ann Arbor, MI (US)
Assigned to The Regents of the University of Michigan, Ann Arbor, MI (US)
Filed by The Regents of the University of Michigan, Ann Arbor, MI (US)
Filed on Feb. 4, 2021, as Appl. No. 17/167,140.
Claims priority of provisional application 62/970,653, filed on Feb. 5, 2020.
Prior Publication US 2021/0338171 A1, Nov. 4, 2021
Int. Cl. G06F 17/00 (2019.01); A61B 5/00 (2006.01); A61B 5/318 (2021.01); G06F 16/908 (2019.01); G06F 17/40 (2006.01); G06N 20/00 (2019.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01)
CPC A61B 5/7264 (2013.01) [A61B 5/318 (2021.01); G06F 16/908 (2019.01); G06F 17/40 (2013.01); G06N 20/00 (2019.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A method of generating an assessment of medical condition for a patient, the method comprising:
obtaining, by a processor, a patient data tensor indicative of a plurality of tests conducted on the patient;
obtaining, by the processor, a set of tensor factors, each tensor factor of the set of tensor factors being indicative of a decomposition of training tensor data for the plurality of tests, the decomposition amplifying low rank structure of the training tensor data;
determining, by the processor, a patient tensor factor for the patient based on the obtained patient data tensor and the obtained set of tensor factors;
applying, by the processor, the determined patient tensor factor to a classifier such that the determined tensor factor establishes a feature vector for the patient, the classifier being configured to process the feature vector to generate the assessment; and
providing, by the processor, output data indicative of the assessment.