Role of Computational Intelligence Techniques in Diagnosing Alzheimer’s disease at Early Stages: A Systematic Literature Review

Computer aided disease diagnosis with computational intelligence research has shown that several intelligent models have been developed to assess medical data and make assumptions about illness severity and early diagnosis. Many researchers find it difficult to anticipate and diagnose the deadly neurodegenerative disorders that fall under the category of dementia using medical image data. Alzhiemers is now the most common dementia, affecting around a third of all people. Many machine learning models have been developed, but there is still a lot of room for further improvement in the field of Alzheimer's disease detection and prevention. This article includes a thorough literature evaluation of machine learning approaches that have been developed to detect Alzheimer's disease at an earlier stage. As a result of these studies, budding Alzheimer's disease researchers will be able to better understand the extent of study in forecasting the illness via the use of artificial neural networks, support vector machines, and deep learning-based ensemble models.