Alzheimer's Prediction: QML for Neuroimaging and Other Biomarkers

Explore the potential of Quantum Machine Learning (QML) in revolutionizing Alzheimer's Disease prediction and early detection through a comprehensive 54-minute video presentation. Delve into three key biomarker areas: language impairment, blood/cerebrospinal fluid analysis, and neuroimaging. Discover how QML can enhance existing machine learning techniques, such as upgrading Support Vector Machines to Quantum Support Vector Machines and leveraging Quantum Convolutional Neural Networks for complex brain imaging data analysis. Gain insights into the latest research on multimodal machine learning approaches that combine MRI, CSF, and genetic information for more accurate Alzheimer's diagnosis. Learn about the potential advantages of quantum computing in optimizing hyperparameters for natural language processing models and improving MR imaging analysis. Understand the significance of biomarkers in Alzheimer's research and how QML can contribute to advancing early detection and prediction methods in this critical field of study.