Early detection of Alzheimer’s disease is essential for improving the quality of life for patients and their families, allowing interventions that can slow the progression of the disease. This research focuses on how artificial intelligence can help identify the early signs of Alzheimer’s through the analysis of clinical and behavioral data. We propose developing an application that, using machine learning algorithms and natural language processing, analyzes information from medical exams, cognitive questionnaires, and daily activity records. Initial results show that it is possible to detect subtle patterns related to the early stages of Alzheimer’s. This tool not only facilitates early diagnosis but also helps monitor the progression of the disease and adjust treatments accordingly. Implementing this technology in daily life could transform the way Alzheimer’s is detected and managed, offering renewed hope to patients and their loved ones. The development of this project by high school students, seeks to apply advanced knowledge of technologies and also create an impact on the community, developing professionals with great knowledge and responsibility for their society.

Keywords: Technology, Alzheimer's, Artificial intelligence, algorithm, education.