INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM

Abstract

Provided are an information processing apparatus, an information processing method, and a program capable of accumulating appropriate relearning data. An information processing apparatus includes an input unit that inputs input data to a learned model acquired in advance through machine learning using learning data, an acquisition unit that acquires output data output from the learned model through the input using the input unit, a reception unit that receives correction performed by a user for the output data acquired by the acquisition unit, and a storage controller that performs control for storing, as relearning data of the learned model, the input data and the output data that reflects the correction received by the reception unit in a storage unit in a case where a value indicating a correction amount acquired by performing the correction for the output data is equal to or greater than a threshold value.

Description

Claims

1. An information processing apparatus comprising: a memory; anda processor, coupled to the memory and configured to: input data into a learned model, wherein the learned model is a machine learning model trained in advance on learning data, wherein the data is a plurality of sets of lesion information and at least one sentence included in a medical diagnostic report based on the lesion information;acquire output data from the learned model through inputting the data including lesion information of a subject to be diagnosed, wherein the output data includes at least one sentence of a medical diagnostic report based on the lesion information of the subject;display the at least one sentence included in the output data on a display;receive correction data for the acquired output data via an input device to generate a corrected output data including an added portion that is added to the at least one sentence included in the output data and a deleted portion that is deleted from the at least one sentence included in the output data;store, as relearning data of the learned model, a set of the input data including the lesion information of the subject and the corrected output data in a storage in a case where a value indicating a correction amount of the added portion and the deleted portion included in the corrected output data is equal to or greater than a threshold value; andretrain the learned model by using the stored relearning data in the storage.

2. The information processing apparatus according to claim 1, wherein the at least one sentence included in the output data indicates features of a fixed phrase of the medical diagnostic report.

3. The information processing apparatus according to claim 1, wherein the lesion information is acquired as a result of a diagnostic support process for a medical image of the subject.

4. The information processing apparatus according to claim 1, wherein the value indicating the correction amount is a sum of an absolute value of a ratio of the added portion to the at least one sentence included in the output data and an absolute value of a ratio of the deleted portion to the at least one sentence included in the output data.

5. The information processing apparatus according to claim 1, wherein the value indicating the correction amount is the number of times the correction is performed by the user for the output data.

6. The information processing apparatus according to claim 1, wherein the threshold value is selected based on a skill level of the user prior to the generation of the relearning data.

7. The information processing apparatus according to claim 1, wherein the threshold value is a value determined depending on a treatment plan of the subject.

8. An information processing method, executed by a computer, comprising: inputting data into a learned model, wherein the learned model is a machine learning model trained in advance on learning data, wherein the data is a plurality of sets of lesion information and at least one of sentence included in a medical diagnostic report based on the lesion information;acquiring output data from the learned model through inputting the data including lesion information of a subject to be diagnosed, wherein the output data includes at least one sentence of a medical diagnostic report based on the lesion information of the subject;displaying the at least one sentence included in the output data on a display;receiving correction data for the acquired output data via an input device to generate a corrected output data including an added portion that is added to the at least one sentence included in the output data and a deleted portion that is deleted from the at least one sentence included in the output data;storing, as relearning data of the learned model, a set of the input data including the lesion information of the subject and the corrected output data in a storage in a case where a value indicating a correction amount of the added portion and the deleted portion included in the corrected output data is equal to or greater than a threshold value, andretraining the learned model by using the stored relearning data in the storage.

9. A non-transitory computer readable medium storing a program causing a computer to execute a process comprising: inputting data into a learned model, wherein the learned model is a machine learning model trained in advance on learning data, wherein the data is a plurality of sets of lesion information and at least one sentence included in a medical diagnostic report based on the lesion information;acquiring output data from the learned model through inputting the data including lesion information of a subject to be diagnosed, wherein the output data includes at least one sentence of a medical diagnostic report based on the lesion information of the subject;displaying the at least one sentence included in the output data on a display;receiving correction data for the acquired output data via an input device to generate a corrected output data including an added portion that is added to the at least one sentence included in the output data and a deleted portion that is deleted from the at least one sentence included in the output data;storing, as relearning data of the learned model, a set of the input data including the lesion information of the subject and the corrected output data in a storage in a case where a value indicating a correction amount of the added portion and the deleted portion included in the corrected output data is equal to or greater than a threshold value; andretraining the learned model by using the stored relearning data in the storage.