Detection Method of Early Data Based on SVM Classifier

Abstract

Alzheimer's disease is a common neurodegenerative disease in the elderly, and timely detection and treatment at the early-stage of the disease can prevent from worsening and promote recovering. Traditional Alzheimer's disease detection methods are costly and technically difficult to achieve. This project mainly explores a method for detecting early Alzheimer's disease based on plasma protein and support vector machine. The specific process is to collect human plasma protein data, extract features and classify it through support vector machine, thereby Check whether it has an early-stage disease. This method has certain advantages over traditional methods in terms of detection cost, accuracy, and difficulty of implementation.