Enhancing Alzheimer's Disease Stage Prediction with Machine Learning and Multi-Agent Systems

As life expectancy continues to rise in modern society, the prevalence of age-related diseases hasalso increased. Alzheimer’s disease (AD), a common form of dementia that primarily affects older adults, isone such condition. AD is a progressive and irreversible brain disorder that gradually impairs memory,thinking, reasoning, and other cognitive abilities. The likelihood of developing Alzheimer's risessignificantly after the age of 65, with the disease's severity worsening over time. Early warning signs of ADinclude poor judgment, emotional changes, difficulty completing familiar tasks, misplacing items, troublesolving problems, and challenges with learning new things. Key risk factors for AD include smoking,hypertension, diabetes, obesity, and advancing age. In recent years, the number of AD patients hasincreased dramatically, particularly in developed countries with longer life expectancies.Machine learning and agent systems have made tremendous strides in various fields, includingweather forecasting, robotics, search engines, natural language processing, speech recognition, medicaldiagnosis, and handwriting recognition. Machine learning, a fundamental component of ArtificialIntelligence (AI), is an evolving technology that enables computers to "learn" by developing classifiers.This technology aims to address problems related to inference and prediction using available data, which isessential for decision-making by humans or intelligent systems like agent systems. An agent system refersto a computer system placed in an environment that can perform flexible, autonomous actions to achieve itsdesign goals. One key feature of agent systems is their ability to demonstrate intelligence throughinteraction. Intelligent agents possess reactive, proactive, and social characteristics. A multi-agent systemconsists of multiple agents that collaborate or compete to accomplish shared objectives.Several researchers have proposed different methods for predicting the stages of Alzheimer'sDisease (AD) using machine learning applied to various diagnostic techniques. While these studies havemade significant progress, some have focused solely on brain imaging scans for diagnosis, while othersrely on specialized devices that require patients to visit healthcare centers for evaluation.