ANALYSIS OF ALGORITHMS FOR PREDICTION AND PRELIMINARY DIAGNOSTICS OF GASTROENTEROLOGICAL DISEASES
Keywords:
KNN, Random , Forest, DNN, ResNet, artificial intelligence, algorithm, gastroenterological diseases, medicineAbstract
This article discusses prediction algorithms for the preliminary diagnosis of gastroenterological diseases. Made analysis of several algorithms such as KNN, Random Forest, DNN, ResNet. Currently, artificial intelligence algorithms are widely used in all industries and give their results.
For example, it increases the efficiency of the staff and reduces the human factor. With the help of some algorithms, it is possible to solve the problem of diagnosing several diseases.
Classification algorithms are used, with the help of classification, the diagnosis system quickly determines the disease and can help the medical staff quickly make a decision and make an accurate diagnosis for a specific disease.
The effectiveness of algorithms in the field of medicine of gastroenterological diseases has been tested and the corresponding results have been obtained. A study was conducted on the composition of human saliva, the characteristics and function of saliva. The parameters of human saliva and how it affects human health have been studied. In this case, an analysis of algorithms for the preliminary diagnosis of a disease of the gastrointestinal tract was made. With the help of saliva, you can pre-diagnose diseases of the gastrointestinal tract. For preliminary diagnosis and determination of diseases of the gastrointestinal tract, the classification algorithms KNN, Random Forest, DNN and ResNet are used.
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