PSB 2019 Workshop on Text Mining and Visualization for Precision Medicine

Graciela Gonzalez-Hernandez, Zhiyong Lu, Robert Leaman, Davy Weissenbacher, Mary Regina Boland, Yong Chen, Jingcheng Du, Juliane Fluck, Casey S. Greene, John Holmes, Aditya Kashyap, Rikke Linnemann Nielsen, Zhengqing Ouyang, Sebastian Schaaf, Jaclyn N. Taroni, Cui Tao, Yuping Zhang, Hongfang Liu

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    Abstract

    Precision medicine, an approach for disease treatment and prevention that considers “individual variability in genes, environment, and lifestyle” 1 was endorsed by the National Institutes of Health, aided by the presidential Precision Medicine Initiative (PMI), in 2016. PMI provided funding for cancer research and for building a national cohort of one million or more U.S. participants, now known as the “All of Us” Research Program, which aims to expand its impact to all diseases. PMI was the catalyst to a widespread effort around precision medicine, as evidenced by the more than 1000 grants funded by different NIH institutes in just the last two years. The data being generated by these efforts is growing exponentially, and becomes both the greatest treasure and the greatest
    challenge for researchers. This workshop is a continuation of a similar session in PSB 2018, providing a forum for researchers with strong background in text mining or natural language processing (NLP) and/or machine learning (ML) who are actively collaborating with bench scientists and clinicians to tackle the challenges brought about by this explosion of data.
    Original languageEnglish
    Title of host publicationPSB 2019 proceedings
    Number of pages6
    PublisherWorld Scientific
    Publication date2018
    Pages449-454
    Publication statusPublished - 2018
    EventPacific Symposium on Biocomputing 2019 - , United States
    Duration: 3 Jan 20197 Jan 2019

    Conference

    ConferencePacific Symposium on Biocomputing 2019
    CountryUnited States
    Period03/01/201907/01/2019

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