Body fluid volume estimation device, body fluid volume estimation method, and non-transitory computer-readable medium

Abstract

A body fluid volume estimation device includes a pre-training unit, a transfer learning unit, and an estimation unit. The pre-training unit performs pre-training by using, as supervised information, information indicating body fluid volumes of the multiple patients when face images of multiple patients are captured. The transfer learning unit further performs transfer learning on multiple face images of one specific patient after the pre-training, and constructs a trained model. The estimation unit estimates, by inputting a face image of the one specific patient to the trained model, a body fluid volume at a point in time at which the face image of the one specific patient is captured. By estimating a body fluid volume from a face image by machine learning, the body fluid volume can be used for assistance such as decision making of a user.

What is claimed is: 
     
         1 . A body fluid volume estimation device comprising:
 at least one memory configured to store instructions; and   at least one processor configured to execute the instructions to:   perform pre-training on face images of multiple patients by using, as supervised information, information including discrete information and continuous information and indicating a body fluid volume of each of multiple patients when the face images of multiple patients are captured;   perform transfer learning on multiple face images of one specific patient after the pre-training, and construct a trained model;   estimate, by inputting a face image of the one specific patient received from an image capturing device to the trained model, a body fluid volume of the one specific patient at a point in time at which the face image of the one specific patient is captured; and   output an estimation result to a display device.   
     
     
         2 . The body fluid volume estimation device according to  claim 1 , wherein
 the information indicating the body fluid volume of each multiple patients when the face images of the multiple patients are captured includes the discrete information indicating presence or absence of a swelling in the face image of each of the multiple patients and the continuous information indicating weight of each of the multiple patients, and   the at least one processor is further configured to execute the instructions to   estimate presence or absence of a swelling and weight of the one specific patient at which the face image of the one specific patient is captured by inputting the face image of the one specific patient to the trained model.   
     
     
         3 . The body fluid volume estimation device according to  claim 2 , wherein
 the at least one processor is further configured to execute the instructions to:   detect, based on a prediction result of the presence or absence of the swelling of the one specific patient, whether the body fluid volume of the one specific patient is changed from a preset standard body fluid volume of the one specific patient, and   acquire, from an estimation result of the weight, a difference in the body fluid volume of the one specific patient from the preset standard body fluid volume.   
     
     
         4 . The body fluid volume estimation device according to  claim 2 , wherein
 the discrete information indicating the presence or absence of the swelling in the face image of each of the multiple patients is label information representing the presence of the swelling, and   the at least one processor is further configured to execute the instructions to perform pre-training in such a way that feature values of face images having the same label information representing the presence or absence of the swelling are brought closer as the continuous information indicating the weight is more similar.   
     
     
         5 . The body fluid volume estimation device according to  claim 2 , wherein the at least one processor is further configured to execute the instructions to perform pre-training by weight-aware supervised momentum contrast (WeightSupMoCo). 
     
     
         6 . The body fluid volume estimation device according to  claim 2 , wherein
 the multiple patients and the one specific patient are a patient who receives dialysis, and   weight of each of the multiple patients and the one specific patient after dialysis associated with a case without a swelling has a value acquired by subtracting a body fluid volume removed by dialysis from weight of each of the multiple patients and the one specific patient before dialysis associated with a case with a swelling.   
     
     
         7 . The body fluid volume estimation device according to  claim 2 , wherein
 the multiple patients and the one specific patient are a patient who receives dialysis, and   weight of each of the multiple patients and the one specific patient before dialysis associated with a case with a swelling has a value acquired by adding a body fluid volume removed by dialysis to weight of each of the multiple patients and the one specific patient after dialysis associated with a case without a swelling.   
     
     
         8 . The body fluid volume estimation device according to  claim 2 , wherein
 the multiple patients and the one specific patient are a patient who receives dialysis, and   weight of each of the multiple patients and the one specific patient before dialysis associated with a case with a swelling has a value acquired by adding a body fluid volume removed by dialysis to preset standard weight of each of the multiple patients and the one specific patient.   
     
     
         9 . The body fluid volume estimation device according to  claim 1 , wherein
 the at least one processor is further configured to execute the instructions to:   store the face images of the multiple patients to be used for pre-training, the information indicating the body fluid volume of the multiple patients when the face images of the multiple patients are captured, and the multiple face images of the one specific patient to be used for the transfer learning,   read the face images of the multiple patients and information indicating the body fluid volume when the face images of the multiple patients are captured, and performs pre-training,   read the multiple face images of the one specific patient, and   perform transfer learning.   
     
     
         10 . A body fluid volume estimation method comprising:
 performing pre-training on face images of multiple patients by using, as supervised information, information including discrete information and continuous information and indicating a body fluid volume of each of the multiple patients when the face images of the multiple patients are captured;   further performing transfer learning on multiple face images of one specific patient after the pre-training, and constructing a trained model;   estimating, by inputting a face image of the one specific patient received from an image capturing device to the trained model, a body fluid volume of the one specific patient at a point in time at which the face image of the one specific patient is captured; and   outputting an estimation result to a display device.   
     
     
         11 . A non-transitory computer-readable medium storing a program causing a computer to execute:
 processing of performing pre-training on face images of multiple patients by using, as supervised information, information including discrete information and continuous information and indicating a body fluid volume of each of the multiple patients when the face images of the multiple patients are captured;   processing of further performing transfer learning on multiple face images of one specific patient after the pre-training, and constructing a trained model;   processing of estimating, by inputting a face image of the one specific patient received from an image capturing device to the trained model, a body fluid volume of the one specific patient at a point in time at which the face image of the one specific patient is captured; and   processing of outputting an estimation result to a display device.