Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A multistage inference system includes a causality expression storage unit that stores a plurality of sentences including a pair of a phrase representing a cause and a phrase representing an effect, and a scenario reliability calculator that calculates a score for evaluating causality chain possibility among the sentences. The score is calculated based on type identity of documents including the sentences or information on authors of the documents.

Abstract: It becomes possible to implement a route search fast, and furthermore routes whose meanings are easy to understand are searched for by linking routes on the basis of relations with similar backgrounds. A provided relevance analyzing device includes a control section and a database. The database stores: node data about nodes on a network representing relevance between a plurality of events, and edge data about edges representing interrelationships between the events. The control section includes: an inter-edge background similarity computing section that computes a similarity between documents corresponding to two edges by using the node data and edge data stored in the database; and a route computing section that computes routes with high similarities as routes on the network.

Abstract: 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.

Abstract: Provided is a trial planning support apparatus, including a processor and a storage unit, wherein the storage unit stores therein data of a plurality of documents about clinical trials implemented in the past, and wherein the processor is configured to receive information about a clinical trial, and search the plurality of documents for a plurality of sentences relevant to the received information, classify the plurality of sentences that have been found by the search into a plurality of clusters based on a degree of similarity, and output information about the sentences classified into clusters.

Abstract: Provided is a training data creation method includes a step to create a training set that includes, as an index term for extracting a document used for learning, one or more of the index terms assigned to applicable documents or non-applicable documents, a step to create the document identification model that learns the document data assigned the index term included in the training set, and create an evaluation value by using the created document identification model to identify prescribed evaluation data, a step to determine whether to use each index term included in the training set for creating the training data on the basis of the evaluation value, and a step to create the training data by adding document data that is assigned an index term determined to be appropriate for use in creating the training data.

Abstract: 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.

Abstract: 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.