Lifelog Data

Lifelog data, encompassing diverse digital records of daily activities and experiences, is increasingly used to understand individual lifestyles and predict health outcomes. Current research focuses on developing sophisticated machine learning models, including deep learning and clustering techniques, to extract meaningful patterns from this high-dimensional data, such as predicting blood biomarkers from activity and sleep patterns or identifying lifestyle profiles from mobility data. These analyses aim to improve personalized healthcare by enabling more accurate risk assessments, earlier disease detection, and tailored preventative strategies, ultimately impacting both clinical practice and public health initiatives.