Hitachi, Ltd.

Shuntaro Yui

Wataru Takeuchi

Shinji Tarumi

Ken Naono

Takuma Shibahara

Junichi Miyakoshi

Kunihiko Kido

Hideyuki Ban

Kazuki Matsuzaki

Jumpei Sato

Takuya Kamiyama

Provided is an integration device that is accessible to statistical information based on analysis target data of each of a plurality of analysis target devices and includes a processor configured to execute a program and a storage device configured to store the program. The integration device executes acquisition processing of acquiring first statistical information and second statistical information from a plurality of pieces of statistical information, integration processing of integrating the first statistical information and the second statistical information acquired by the acquisition processing by statistical processing based on the number of first data of first analysis target data used for statistical processing of the first statistical information and the number of second data of second analysis target data used for statistical processing of the second statistical information, and output processing of outputting integration statistical information obtained by the integration processing.

Integration device, integration method, and storage medium

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.

Analysis apparatus and analysis method

The task is to provide a system which supports smooth patient referral from a referral source medical institution to a referral destination medical institution and which particularly prevents readmission due to cases that are difficult to determine simply based on patient attributes or due to the quality of medical services. To achieve this task, a referral difficult degree calculation unit calculates a referral difficulty degree which quantifies the risk that a patient cannot be discharged because a referral destination cannot be found, in consideration of a readmission risk calculated by a readmission risk calculation unit, the geographical distance between the patient and the referral destination medical institution, the total number of patients accepted, and the number of beds available. This referral difficulty degree is outputted to an output unit of the referral source medical institution or the referral destination medical institution.

Regional medical cooperation system

Provided is a region extraction system that uses an image data analysis process, which has overcome the problem of false positives in region extraction and assists in more accurate region extraction. A luminance distribution-analyzing unit () is used to determine a parameter of unknown quantity for extracting a region of interest. The luminance distribution-analyzing unit () searches a luminance distribution management database () for a region, which has a luminance distribution similar to the region of interest and is easily extracted, as a similar area. The region of the similar area is extracted using a region extraction pre-processing unit () and the value of the parameter of unknown quantity is determined on the basis of an image feature value calculated from the region extraction results.

Region extraction system

Growing community of inventors

Tokyo, Japan

Shuntaro Yui