Peritoneal dialysis mode auxiliary recommendation system based on variational inference and deep learning

Abstract

The invention discloses a peritoneal dialysis treatment effect prediction system based on variational inference and deep learning. The system comprises an information acquisition module, a calculationprocessing module, an auxiliary recommendation module and a self-learning module; the calculation processing module adopts a prediction model based on variational inference and deep learning; the process comprises the steps of obtaining a retrospective experiment data set; performing deriving to obtain a variation lower bound, and converting the maximum likelihood function into the maximum variation lower bound; constructing a corresponding model, and taking maximization of a variation lower bound as an optimization target; selecting an optimal hyper-parameter combination by using hyper-parameter search; and testing a model which adopts optimal hyper-parameter training on the test set. The model can predict the expected treatment effect difference of automatic peritoneal dialysis and manual peritoneal dialysis for an individual under the condition of giving individual characteristics, and decouples hidden variables through a variational inference method, so that the influence of selection bias errors on prediction is reduced, and more accurate prediction performance is obtained. And a decision maker can be better assisted in selecting a treatment mode.

Description

technical field [0001] The invention relates to the field of peritoneal dialysis artificial intelligence, in particular to a peritoneal dialysis mode auxiliary recommendation system based on variational inference and deep learning. Background technique [0002] Peritoneal dialysis, hemodialysis, and kidney transplantation are currently the three main treatments for patients with end-stage renal disease. Due to the shortage of kidney sources, the number of patients undergoing kidney transplantation is decreasing, and the number of patients in hemodialysis centers at all levels is gradually becoming saturated. Peritoneal dialysis is being used by more and more patients. Peritoneal dialysis is divided into manual peritoneal dialysis and automatic peritoneal dialysis. In recent years, with the development of technology and the continuous improvement of people's living standards, the proportion of automatic peritoneal dialysis has increased year by year. However, compared with ma...

AI Technical Summary

Problems solved by technology

In this case, there are differences in the distribution between the groups of different intervention programs, and this difference will be introduced when estimating ITE through the above method, resulting in incorrect estimation of ITE

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