Multimodal Neuroimaging and Quantum Machine Learning for Alzheimer's Detection

Explore a comprehensive 1 hour 32 minute conference talk on multimodal neuroimaging and quantum machine learning (QML) for Alzheimer's disease. Delve into the history of artificial intelligence in medicine and the advantages of multimodal neuroimaging techniques. Examine the industry strategy of balancing performance and portability in neuroimaging devices, considering quantum technologies. Learn about ChemicalQDevice's QML Stage I/II forecasted algorithms and their potential applications in the industry, including opportunities for standards, protocols, and competitive advantage. Analyze research from multiple datasets on multimodal MRI neuroimaging for Alzheimer's disease detection. Gain insights into the combination of various neuroimaging techniques, such as EEG and fMRI, to obtain more detailed information about brain dynamics. Access additional references on multimodal neuroimaging, including examples from Stanford Health Care and pediatric applications.