TY - JOUR
T1 - PSB 2019 workshop on text mining and visualization for precision medicine
AU - Gonzalez-Hernandez, Graciela
AU - Lu, Zhiyong
AU - Leaman, Robert
AU - Weissenbacher, Davy
AU - Boland, Mary Regina
AU - Chen, Yong
AU - Du, Jingcheng
AU - Fluck, Juliane
AU - Greene, Casey S.
AU - Holmes, John
AU - Kashyap, Aditya
AU - Nielsen, Rikke Linnemann
AU - Ouyang, Zhengqing
AU - Schaaf, Sebastian
AU - Taroni, Jaclyn N.
AU - Tao, Cui
AU - Zhang, Yuping
AU - Liu, Hongfang
N1 - Funding Information:
† Work partially supported by the National Library of Medicine of the National Institutes of Health (NIH) under grant number R01LM011176 (GGH) and its Intramural Research Program (ZL and RL). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Publisher Copyright:
© 2018 The Authors.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
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M3 - Conference article
C2 - 30864346
AN - SCOPUS:85062763569
SN - 2335-6936
VL - 24
SP - 449
EP - 454
JO - Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
JF - Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
IS - 2019
T2 - 24th Pacific Symposium on Biocomputing, PSB 2019
Y2 - 3 January 2019 through 7 January 2019
ER -