Kidney replacement therapy starting strategy evaluation method and device and electronic equipment

A technique for initiating strategies, therapies, applied in the field of machine learning

Pending Publication Date: 2020-09-08
戴松世
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In view of this, the purpose of the embodiments of the present application is to provide a method, device and electronic equipment for evaluating the start-up strategy of renal replacement therapy, so as to improve the accuracy of the prediction results of RRT start-up timing in the prior art

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  • Kidney replacement therapy starting strategy evaluation method and device and electronic equipment
  • Kidney replacement therapy starting strategy evaluation method and device and electronic equipment
  • Kidney replacement therapy starting strategy evaluation method and device and electronic equipment

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Embodiment Construction

[0041] The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

[0042] The applicant has found that many diseases, such as acute kidney injury (Acute Kidney Injury, AKI), have high clinical heterogeneity, and the distinction between "early" and "late" RRT is variable, and attempts are made based on traditional Parameters such as serum creatinine (SCr) or urine output (UO) may not be accurate. Furthermore, it is unclear whether the "optimal timing" of RRT would be due to early clearance of uremia, appropriate volume management, attenuation of inflammatory processes, or any other effect that has not been fully elucidated. Several models adopted by the industry, such as using random forests, extreme gradient boosting, and artificial neural networks to predict AKI (or include RRT), do not consider treatment response and state changes, and therefore, are not suitable...

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Abstract

The invention provides a kidney replacement therapy starting strategy evaluation method and device and electronic equipment, and relates to the technical field of machine learning. The method comprises the following steps: based on patient data, determining a life state prediction result of a patient by adopting a life state monitoring model; and inputting the life state prediction result into a kidney replacement therapy RRT starting strategy evaluation model to obtain an RRT starting strategy evaluation result output by the RRT starting strategy evaluation model, the evaluation result comprising indication information about whether to suggest starting of RRT. According to the method, whether the RRT is suggested to be started or not is determined by adopting the RRT starting strategy evaluation model according to the life state of a patient, so that the prediction accuracy and the prediction efficiency of the RRT starting opportunity are improved.

Description

technical field [0001] The present application relates to the technical field of machine learning, and in particular, relates to a method, device and electronic device for evaluating a strategy for initiating renal replacement therapy. Background technique [0002] Renal replacement therapy (Renal Replacement Therapy, RRT) technology has been widely used in patients with acute kidney injury (AKI) to improve the prognosis, and is an important means of support in the treatment of acute kidney injury. However, reliable tools for predicting the need for RRT based on pre-defined diagnostic thresholds for individual parameters (such as serum creatinine or urea) are extremely limited, given the wide variability in the clinical presentation of intensive care patients. Since the acceptance of the KDIGO AKI criteria, a number of randomized trials have evaluated the optimal timing of RRT initiation, including initiation of renal replacement therapy in early or late stages in critically...

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Application Information

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IPC IPC(8): G16H50/70G16H50/20G16H80/00G06N3/08
CPCG16H50/70G16H50/20G16H80/00G06N3/08Y02A90/10
Inventor 戴松世
Owner 戴松世
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