Urine Output Prediction Model Using Multi-Timepoint Patient Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing physical condition estimating systems fail to consider the output of predicted future urine output based on multiple urine outputs measured from the same patient within a predetermined period.
Innovation Solution
A computer program and information processing method that utilize a prediction model to output a predicted urine output by acquiring and processing urine output data from the same patient at multiple time points, using a neural network to forecast the urine output a predetermined time ahead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a prediction model is introduced to output predicted future urine output based on multiple urine outputs measured from the same patient, then the ability to predict future urine output patterns is improved, but the device complexity increases
Solution Approach 1:
The system performs preliminary learning by collecting and processing multiple urine output measurements from the same patient over a predetermined period to build a prediction model. This preliminary action enables the system to predict future urine output patterns by analyzing historical data trends, thereby improving prediction reliability while managing complexity through pre-processing and model training phases.
2Reliability
If multiple urine output measurements from the same patient are collected and processed, then the prediction reliability is improved, but the data processing complexity increases
Solution Approach 1:
The system segments the data processing by dividing urine output measurements into distinct time periods and organizing them by individual patient identifiers. This segmentation allows the prediction model to process multiple measurements systematically, improving reliability through structured analysis while reducing processing complexity through organized data management and modular computation approaches.
Data Source
Figure 1~2
Figure 3
Figure 4
AI summary
A computer program causes a computer to perform a process including: acquiring information regarding urine outputs measured from the same patient at a plurality of time points within a predetermined period; inputting the acquired information regarding the urine outputs measured at the plurality of time points to a prediction model that has learned to output information regarding a predicted urine output a predetermined elapsed time ahead when the information regarding the urine outputs measured at the plurality of time points is input; acquiring the information regarding the predicted urine output the predetermined elapsed time ahead, from the prediction model; and outputting the acquired information regarding the predicted urine output.