As a knowledge representation tool, knowledge graph (KG) has been widely used. In this study, a question answering (Q&A) system for geriatric diseases based on knowledge graph was constructed to help the elderly obtain medical information. Initially, a total of 6,376 disease data items were collected and analyzed in order to identify the characteristics of these diseases. Then, the KG is constructed by Neo4j graph database. The establishment of Q&A system starts from semantic recognition. The Aho-Corasick (AC) automaton is utilized to filter user input questions. The Cypher language is employed for querying graph databases, and the obtained results are then imported into predefined templates for output. The accuracy of our system for different categories of questions is 87% and 94%, respectively. Finally, the random forest model is introduced to solve the problem of disease diagnosis. The feature variables were vectorized using TF-IDF model and the target variables were vectorized using one-hot model. In general, we introduce a novel Knowledge graph-driven Q&A system. Provide a new tool for health management of the elderly population. And the construction of Q&A system will promote the development of smart medicine and solves the health confusion of the elderly.