Hitachi, Ltd.

Hiroko Otaki

Kunihiko Kido

In screening of documents based on a similarity between keywords, it is difficult to exclude documents having similar background but different conclusions. In a document review assistance method executed by a computer system, a storage unit stores data on a plurality of documents, and the document review assistance method includes: a step of creating, by a control unit, a sentence vector based on a sentence included in the plurality of documents; a step of classifying, by the control unit, the plurality of documents into a plurality of clusters based on the created sentence vector; a step of specifying, by the control unit, a subgraph on a network of a word in a first document set included in at least one of the clusters; and a step of controlling, by the control unit, the creation of the sentence vector based on the specified subgraph.

Document review assistance method, document review assistance system, and non-transitory computer readable medium

A sentence classification apparatus, a sentence classification method, and a sentence classification program that can appropriately classify sentences by adjusting parameters are provided. The sentence classification apparatus includes: a case sentence obtention unit for obtaining plural case sentences which are associated with effect values that are values obtained by evaluating effects; a case value creation unit for creating case values obtained by numerizing the case sentences for each of parameters with different values; a correlation coefficient calculation unit for calculating a correlation coefficient between the case values and the effect values for each of the values of the parameters; and a parameter selection unit for selecting a parameter among the parameters with different values on the basis of the correlation coefficient.

Sentence classification apparatus, sentence classification method, and sentence classification program

A processor is configured to: acquire clinical information containing cases each indicating a disease of a patient and a medical care event performed on the patient; acquire literature information containing literature indicating a name of the disease and a word indicating the medical care event; calculate a frequency of one case indicating a combination of a plurality of diseases based on the clinical information; analyze the literature information using each of the name of the disease and the word indicating the medical care event; acquire a criterion for determining a disease for which the medical care event has been performed; acquire first relevance information indicating whether the medical care event has been performed for the disease based on the analysis result, the calculated frequency and the acquired criterion; and generate medical information indicating a relationship between the medical care event and the disease based on the first relevance information.

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Tokyo, Japan

Hiroko Otaki