Abstract: A document creation support apparatus acquires document information associated with an input target person, derives the number of pieces of examination information included in the document information for each examination item, and derives a degree of importance of the examination item for the target person based on the derived number of pieces of the examination information.

Abstract: A document creation support apparatus displays a subject document creation screen for creating a subject document and a reference document display screen for displaying a reference document to be used for creating the subject document, and in a case where a plurality of the reference documents are displayed on the reference document display screen, displays an overlapping part included in the reference document in a non-highlighted manner with respect to a non-overlapping part.

Abstract: A document presentation apparatus acquires date information based on text information included in a document, extracts a plurality of the documents based on a set condition, and presents the document of which an evaluation value based on the date information acquired for each of the plurality of extracted documents is relatively high with priority over the document of which the evaluation value is relatively low.

Abstract: An information processing apparatus generates a first character string set by dividing first document data into different lengths, derives an evaluation value of each character string constituting the first character string set by using the first character string set and second document data created from the first document data in accordance with a purpose, and selects, based on the derived evaluation value, a plurality of character strings from the first character string set as correct answer data of a generative model that receives input of document data and outputs a second character string set including a plurality of character strings included in the input document data.

Abstract: An information processing apparatus acquires document data, and an item and a numerical value which are associated with each other, and extracts, in a case in which a second numerical value within an allowable range including an acquired first numerical value is included in the document data, a phrase existing around the second numerical value included in the document data as a candidate for a synonymous term of the item.

Abstract: A prediction device that predicts information related to a patient based on medical data of the patient, including: a processor; and a memory connected the processor, in which the processor being configured to execute: data set extraction processing of extracting M data sets by classifying pieces of medical data of plural patients into any one of M types of predetermined attributes, training data set generation processing of generating M training data sets related to the M types of attributes from the M data sets, similarity calculation processing of calculating, for each pair of the M types of attributes, a similarity between the attributes, training processing of training one or plural machine learning models based on the similarity between the attributes by using the M training data sets, and prediction processing of causing the one or plural machine learning models to predict the information related to the patient.

Abstract: There is provided a device for generating a data merging rule for a machine learning model, the device including: a processor, and a memory connected to or built in the processor, in which the processor is configured to execute specifying processing of specifying a combination of feature vectors that are included in a data set including a correct answer label and are allowed to be merged, and rule generation processing of generating a merging rule of the feature vectors based on a combination of the feature vectors that are allowed to be merged.

Abstract: There is provided a device for determining an execution order of a plurality of tasks, the device including: processor; and a memory connected to or built in the processor, in which the processor is configured to execute execution order determination processing of determining an execution order of the plurality of tasks under a condition that an output of at least one task of the tasks is input to the task in a subsequent stage.

Abstract: An information processing apparatus including: plural models including at least a first model that uses first data as input to carry out a first prediction task and a second model that uses second data as input to carry out a second prediction task different from the first prediction task, and at least one processor, in which the processor is configured to: acquire information data representing information related to a specific target; select a selection model to be used for prediction from among the plural models based on the information data; and derive a degree of importance to the specific target for each item included in the information data by using the selection model.

Abstract: An information processing apparatus includes at least one processor, in which the processor is configured to: for a machine learning model that uses a document data group including a plurality of document data as input and outputs output data, derive an evaluation value in the machine learning model for each document data included in the document data group.

Abstract: A model generation apparatus includes a processor that is configured to: acquire information data for learning, acquire document data for learning, extract a first portion and a second portion having a lower rate of match with the information data than the first portion from the document data based on a rate of match between the information data and each portion of the document data, generate a first machine learning model by using first learning data in which first data for learning included in the information data is used as input data and the first portion is used as correct answer data, and generate a second machine learning model by using second learning data in which second data for learning included in the information data is used as input data and the second portion is used as correct answer data.