	US 12,106,202 B2
	Machine-learning method and system to optimize health-care resources using doctor-interpretable entity profiles
Zhao Xu, Heidelberg (DE); and Giuseppe Serra, Heidelberg (DE)
Assigned to NEC LABORATORIES EUROPE GMBH, Heidelberg (DE)
Filed by NEC Laboratories Europe GmbH, Heidelberg (DE)
Filed on Jun. 21, 2023, as Appl. No. 18/338,384.
Application 18/338,384 is a continuation of application No. 16/841,762, filed on Apr. 7, 2020, granted, now 11,727,248.
Prior Publication US 2023/0334286 A1, Oct. 19, 2023
Int. Cl. G06N 3/04 (2023.01); G06N 3/08 (2023.01)

CPC G06N 3/04 (2013.01) [G06N 3/08 (2013.01)]

20 Claims

1. A method for extracting human-interpretable entity profiles from a text-labeled data graph of a system comprised of entities, the method comprising:

obtaining a data graph associated with a smart hospital, the data graph comprising nodes representing the entities and edges between the nodes representing links between the entities, and

extracting the human-interpretable entity profiles from a tensor that has been learned, using a neural network, to capture patterns among text associated with the edges between respective pairs of the nodes, wherein neural network layers of the neural network are constructed such that the edges are modeled as a function of the associated text and cluster representations of the respective pairs of the nodes.