Advances in Text Mining and Visualization for Precision Medicine

• Type of Material: Conference Paper
• Authors: Graciela Gonzalez-Hernandez, University of Pennsylvania; Md. Abeed Sarker, Emory University; Karen O'Connor, University of Pennsylvania; Casey Greene, University of Pennsylvania; Hongfang Liu, Mayo Clinic
• Language: English
• Date: 2018-01-01
• Publisher: Emory University Libraries
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: Open Access chapter published by World Scientific Publishing Company
• License: Creative Commons Attribution-NonCommercial 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1142/9789813235533_0051
• Title of Journal or Parent Work: PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018 (PSB)
• Conference or Event Name: 23rd Pacific Symposium on Biocomputing (PSB)
• Volume: 0
• Issue: 212669
• Start Page: 559
• End Page: 565
• Grant/Funding Information: Work partially supported by the National Institute of Allergy And Infectious Diseases (NIAID) of the National Institutes of Health (NIH) under grant number R01AI117011. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
• Keywords: Mathematical & Computational Biology; natural language processing; personalized medicine; visualization; SOFTWARE; Science & Technology; precision medicine; Text mining; biomedicine; Life Sciences & Biomedicine
• Research Categories: Computer Science; Engineering, Biomedical

Abstract

According to the National Institutes of Health (NIH), precision medicine is “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.” Although the text mining community has explored this realm for some years, the official endorsement and funding launched in 2015 with the Precision Medicine Initiative are beginning to bear fruit. This session sought to elicit participation of researchers with strong background in text mining and/or visualization who are actively collaborating with bench scientists and clinicians for the deployment of integrative approaches in precision medicine that could impact scientific discovery and advance the vision of precision medicine as a universal, accessible approach at the point of care.