i2B2 is an NIH-funded National Center for Biomedical Computing. It has periodically staged NLP challenges to extract fine -grained information from clinical records. One such challenge was to identify the information that is medically relevant to identifying heart disease risk over sets of longitudinal patient records. The relevant information may include high blood pressure and cholesterol levels, obesity, smoking status, etc. In this demonstration, we show how our NLP and AI capabilities can identify and extract the necessary information from free text clinical record.