Neurasthenia prediction method and prediction system based on incremental neural network model

Abstract

The invention discloses a neurasthenia prediction method based on an incremental neural network model. The neurasthenia prediction method comprises following steps that a database of neurasthenia daily data is established; a neural network model is trained; daily life data is acquired and sent to a server, and is saved to a user daily data recording chart; intraday data is extracted from the user daily data recording chart to form an n-dimensional vector, after normalization processing, the n-dimensional vector is input into a neurasthenia pathology neural network model to carry out neurasthenia probability prediction; whether the neurasthenia probability value is larger than 0.5 or not is determined by an intelligent household neurasthenia nursing device; when that the user suffers from neurasthenia is determined, the user goes to the hospital for check-up himself, and sends the check-up result back to the server through the intelligent household neurasthenia nursing device, and the server determines whether the check-up result is correct or not; when the check-up result is wrong, an incremental algorithm is executed, and the neural network model is dynamically corrected. The neurasthenia prediction method based on the incremental neural network model is accurate in prediction, and the neural network model is customized for each user.

Description

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AI Technical Summary

Benefits of technology

This patented technology helps healthcare providers make informed decisions about which treatments are best given based on their patient's history or physical examination results. It also provides an accurate way to identify specific causes of neurological disorders such as Parkinson disease (PD) and Alzheimer diseases. By learning from this dataset over many years with new models trained during testing, researchers may improve understanding how they develop effective therapies against those conditions.

Problems solved by technology

This patented technical problem addressed by this patents relates to improving the accuracy of diagnosing neurologically impaired individuals through advanced methods that involve analyzing their behavioral patterns or genetic material for correlations with various factors such as illnesses or drug treatments. Current models are often complicated and require extensive manual effort from users who may lack relevant knowledge about how they react on these drugs overtime.

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