公开(公告)号：US11526722B2

公开(公告)日：2022-12-13

申请号：US16117260

申请日：2018-08-30

Applicant: HITACHI, LTD.

Inventor： Takuma Shibahara ,  Mayumi Suzuki ,  Ken Naono

IPC: G06N3/04 ,  G06N3/08

Abstract: Facilitation of an explanation about an object to be analyzed is realized with high accuracy and with efficiency.
A data analysis apparatus is disclosed which uses a first neural network configured with an input layer, an output layer, and two or more intermediate layers provided between the input layer and the output layer. Each performs a calculation by giving data from a layer of a previous stage and a first learning parameter to a first activation function and outputs a calculation result to a layer of a subsequent stage. The data analysis apparatus includes a conversion section; a reallocation section; and an importance calculation section.

公开(公告)号：US20190122097A1

公开(公告)日：2019-04-25

申请号：US16117260

申请日：2018-08-30

Applicant: HITACHI, LTD.

Inventor： Takuma Shibahara ,  Mayumi Suzuki ,  Ken Naono

IPC: G06N3/04 ,  G06N3/08

Abstract: Facilitation of an explanation about an object to be analyzed is realized with high accuracy and with efficiency.A data analysis apparatus is disclosed which uses a first neural network configured with an input layer, an output layer, and two or more intermediate layers provided between the input layer and the output layer. Each performs a calculation by giving data from a layer of a previous stage and a first learning parameter to a first activation function and outputs a calculation result to a layer of a subsequent stage. The data analysis apparatus includes a conversion section; a reallocation section; and an importance calculation section.

公开(公告)号：US11527325B2

公开(公告)日：2022-12-13

申请号：US16245096

申请日：2019-01-10

Applicant: Hitachi, Ltd.

Inventor： Wataru Takeuchi ,  Takuma Shibahara ,  Ken Naono ,  Shinji Tarumi ,  Shuntaro Yui

IPC: G16H50/20 ,  G06N3/02 ,  G16H50/50 ,  G16H50/70

Abstract: An analysis apparatus comprises: a generation module configured to generate a second piece of input data having a weight for a first feature item of a patient based on: a first piece of input data relating to the first feature item; a second feature item relating to a transition to a prediction target in a clinical pathway relating to a process for diagnosis or treatment; and a clinical terminology indicating relevance between medical terms; a neural network configured to output, when being supplied with the first piece of input data and the second piece of input data generated, a prediction result for the prediction target in the clinical pathway and importance of the first feature item; an edit module configured to edit the clinical pathway based on the prediction result and the importance output from the neural network; and an output module configured to output an edit result.