Senile caries attack prediction system based on generalized regression neural network

• Main Authors: WU WEI, LIU LU, YIN ZHIHUA
• Format: Patent
• Language: Chinese; English
• Published: 29.11.2019
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; PHYSICS

The invention provides a senile caries attack prediction system based on a generalized regression neural network to realize early prediction of senile caries attack, and the system comprises a variable collection module which can collect a variable that can reflect a risk factor that the senile caries is liable to occur and has statistical significance in chi-square test; and an attack predictionmodule used for predicting whether the senile caries occurs or not by using a generalized regression neural network and the acquired variables. The system provided by the invention can provide effective and accurate information for predicting whether the senile caries occurs or not, construction of the prediction model by using biological mathematical modeling plays a positive role in screening ofhigh-risk groups and early diagnosis and treatment of diseases of the senile caries, cross advantages of subjects are fully exerted, and the prediction accuracy is improved on the basis of defining risk factors of the senile