Brainwaves and Soundwaves: A Deep Learning Approach to Alzheimer’s Detection

Cognitive abilities, and the capacity to perform everyday tasks. Early diagnosis is crucial in managing the disease effectively, but it remains a challenge. In recent years, deep learning has shown promise in aiding medical diagnoses, particularly through the analysis of complex data. This project explores a new approach to detecting Alzheimer’s by combining brain MRI scans and speech spectrograms. Using deep learning models, this research examines how well these two different types of data can identify Alzheimer’s, both individually and together. By integrating these datasets using the Keras Functional API, the goal is to enhance diagnostic accuracy, offering a potentially more reliable and non-invasive method for early detection. The hope is that this research will contribute valuable insights to the fight against Alzheimer’s, helping to improve early diagnosis and, ultimately, patient care.