Dementia is one of the major causes of disability and dependency among older people. Early detection is the key for preserving the quality of life of the patients and reducing caring costs. The Clock Drawing Test (CDT) is commonly used by clinicians to screen for early signs of dementia. We build an automated CDT that runs on mobile platforms, enabling convenient and frequent self-monitoring and testing at minimal costs. Our system combines both a spatial-temporal approach and a purely image-based deep learning approach to analyze and evaluate the hand-drawn clocks based on established clinical criteria. Our system produces scores that are highly correlated with expert human raters.