Dina and her team work to develop a single platform for the public to explore NLM resources. Their long-term goal is to create one entry point for all NLM resources. The team is united by the task of enabling computers to understand health-related information needs and the socioeconomic and professional status of NLM users. Dr. Demner-Fushman uses advanced artificial intelligence (AI), natural language processing, and data mining techniques to answer questions about a variety of health topics. Her team developed approaches to predict the course of disease, extract key information from text, summarize documents, answer clinical questions, and retrieve information in multiple ways. Her research led to the current iteration of the MEDLINE resource, which helps people navigate a plethora of NLM resources, as well as Open-i, which helps finding biomedical images.
- Demner-Fushman D, Mrabet Y, Ben Abacha A. Consumer health information and question answering: helping consumers find answers to their health-related information needs. J Am Med Inform Assoc. 2020;27(2):194-201.
- Demner-Fushman D, Chapman WW, McDonald CJ. What can natural language processing do for clinical decision support? J Biomed Inform. 2009;42(5):760-72.
- Goodwin TR, Demner-Fushman D, Lo K, Wang LL, Dang HT, Soboroff IM. Automatic question answering for multiple stakeholders, the epidemic question answering dataset. Sci Data. 2022;9(1):432.
- Roberts K, Alam T, Bedrick S, Demner-Fushman D, Lo K, Soboroff I, Voorhees E, Wang LL, Hersh WR. Searching for scientific evidence in a pandemic: An overview of TREC-COVID. J Biomed Inform. 2021;121:103865.
- Demner-Fushman D, Elhadad N. Aspiring to Unintended Consequences of Natural Language Processing: A Review of Recent Developments in Clinical and Consumer-Generated Text Processing. Yearb Med Inform. 2016;(1):224-233.
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This page was last updated on Wednesday, May 10, 2023