We present a recommender system, PubMedReco, for real-time suggestions of medical articles from PubMed, a database of over 23 million medical citations. PubMedReco can recommend medical article citations while users are conversing in a synchronous communication environment such as a chat room. Normally, users would have to leave their chat interface to open a new web browser window, and formulate an appropriate search query to retrieve relevant results. PubMedReco automatically generates the search query and shows relevant citations within the same integrated user interface. PubMedReco analyzes relevant keywords associated with the conversation and uses them to search for relevant citations using the PubMed E-utilities programming interface. Our contributions include improvements to the user experience for searching PubMed from within health forums and chat rooms, and a machine learning model for identifying relevant keywords. We demonstrate the feasibility of PubMedReco using BMJ's Doc2Doc forum discussions.
Keywords: Information Storage and Retrieval; Medical Informatics Applications; PubMed.