Cerebrospinal Fluid

Cerebrospinal fluid (CSF) research focuses on understanding its role in brain health and disease, particularly its involvement in waste clearance and its biomarker potential for conditions like Alzheimer's disease. Current research employs machine learning techniques, including deep learning models like U-nets and ensemble methods, along with topological data analysis and novel neural network architectures, to analyze CSF flow patterns, biomarker levels, and cellular composition from various imaging and flow cytometry data. These advancements aim to improve the accuracy and efficiency of disease diagnosis, monitor disease progression, and ultimately enhance the development and evaluation of therapeutic interventions.