Hemodialysis treatment scheme assistant decision-making method

A hemodialysis and treatment plan technology, applied in the field of intelligent analysis, can solve problems such as not considering the time series characteristics of hemodialysis medical record data, poor fitting of complex models, etc.

Pending Publication Date: 2020-04-17
BEIJING UNIV OF TECH
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Problems solved by technology

This method does not consider the time-series characteristics of hemodialysis medical record data, and its

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  • Hemodialysis treatment scheme assistant decision-making method
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  • Hemodialysis treatment scheme assistant decision-making method

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[0044] The following will be combined with Figure 1-Figure 4 The present invention is described in detail, and the technical solutions in the embodiments of the present invention are clearly and completely described. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0045] refer to figure 1 , the present invention here provides a kind of hemodialysis treatment scheme assistant decision-making method based on Attention-LSTM, comprises the following steps:

[0046] Step 1: preprocessing the hemodialysis historical medical record data marked by a professional dialysis physician to obtain a total sample set;

[0047] Step 2: Establish a long-short-term memory network based on the self-attention mechanism, ...

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Abstract

The invention discloses a hemodialysis treatment scheme auxiliary decision-making method based on an Attention-LSTM model. The method comprises the following steps: 1, preprocessing hemodialysis historical medical record data labeled by a professional dialysis doctor to obtain a total sample set; 2, establishing a long-short-term memory network based on a self-attention mechanism, and allocating attention weight alphat to each time sequence medical record of an input model so as to calculate a medical record information global feature vector c; 3, inputting the global feature vector c into a multi-task sharing layer to learn a scheme label; and 4, allocating a weight lambdan to the loss of each learning task, and taking the weighted sum of the loss as the total loss; and updating network parameters of the model by using an Adam optimization algorithm to obtain a final hemodialysis treatment scheme auxiliary decision-making model. The model can assist a dialysis clinician in making an individualized hemodialysis treatment scheme for a patient, the manual workload of the clinician is reduced, and the hemodialysis efficiency of a hemodialysis center is improved.

Description

technical field [0001] The invention relates to the field of intelligent analysis, in particular to an Attention-LSTM-based auxiliary decision-making method for a hemodialysis treatment plan. Background technique [0002] Hemodialysis is one of the renal replacement therapies for patients with acute and chronic renal failure. It slowly draws the blood out of the vascular access through the hemodialysis machine, exchanges materials with the dialysate through the principles of diffusion, ultrafiltration, adsorption and convection, removes metabolic waste in the body, maintains electrolyte and acid-base balance, and returns the purified blood to the hospital. Injected into the body. Traditionally, hemodialysis physicians formulate individualized hemodialysis programs for patients based on their own clinical experience. The doctor formulates an individualized hemodialysis plan with reference to the age, weight, renal function, blood routine, electrolytes, cardiac function and ...

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Application Information

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IPC IPC(8): G16H20/40G16H50/70G06N3/04G06N3/08
CPCG16H20/40G16H50/70G06N3/084G06N3/045
Inventor 王冠宋胜男
Owner BEIJING UNIV OF TECH
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