Screening method for congenital cataract risk degree and device thereof
A technology for congenital cataracts and high risk, applied in the medical field, can solve the traumatic and costly problems of pregnant women and babies
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Embodiment 1
[0066] figure 1The method for screening the risk of congenital cataract provided by Embodiment 1 of the present invention.
[0067] refer to figure 1 , the method includes the following steps:
[0068] Step S101, obtaining samples to be classified;
[0069] Step S102, classifying the samples to be classified by machine learning method to obtain classification prediction results;
[0070] Step S103, determining the screening result according to the classification prediction result;
[0071] Among them, the screening results include normal and congenital cataracts.
[0072] Further, samples to be classified include normal samples and congenital cataract samples, and machine learning methods include naive Bayesian methods, refer to figure 2 , step S102 includes the following steps:
[0073] Step S201, calculating the first probability corresponding to each attribute in the normal sample;
[0074] Step S202, calculating the second probability corresponding to each attribut...
Embodiment 2
[0107] Figure 4 It is a schematic diagram of the screening device for the risk of congenital cataract provided by the embodiment of the present invention.
[0108] refer to Figure 4 , the device includes an acquisition unit 10 , a classification unit 20 and a screening result determination unit 30 .
[0109] An acquisition unit 10, configured to acquire samples to be classified;
[0110] A classification unit 20, configured to classify the samples to be classified by a machine learning method to obtain classification prediction results;
[0111] A screening result determining unit 30, configured to determine the screening result according to the classification prediction result;
[0112] Among them, the screening results include normal results and congenital cataract results.
[0113] Further, the machine learning method includes a random forest method, and the classification unit 20 includes:
[0114] Calculate the first probability corresponding to each attribute in t...
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