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

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 language	English
Title of host publication	PSB 2019 proceedings
Number of pages	6
Publisher	World Scientific
Publication date	2018
Pages	449-454
Publication status	Published - 2018
Event	Pacific Symposium on Biocomputing 2019 - Fairmont Orchid, Big Island, United States Duration: 3 Jan 2019 → 7 Jan 2019

Conference

Conference	Pacific Symposium on Biocomputing 2019
Country/Territory	United States
City	Fairmont Orchid, Big Island
Period	03/01/2019 → 07/01/2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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https://psb.stanford.edu/psb-online/proceedings/psb19/

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Gonzalez-Hernandez, G., Lu, Z., Leaman, R., Weissenbacher, D., Boland, M. R., Chen, Y., Du, J., Fluck, J., Greene, C. S., Holmes, J., Kashyap, A., Nielsen, R. L., Ouyang, Z., Schaaf, S., Taroni, J. N., Tao, C., Zhang, Y., & Liu, H. (2018). PSB 2019 Workshop on Text Mining and Visualization for Precision Medicine. In PSB 2019 proceedings (pp. 449-454). World Scientific. https://psb.stanford.edu/psb-online/proceedings/psb19/

@inproceedings{3a2d4f5f34e84e77ad3dd52ba3a56377,

title = "PSB 2019 Workshop on Text Mining and Visualization for Precision Medicine",

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 greatestchallenge 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.",

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

year = "2018",

language = "English",

pages = "449--454",

booktitle = "PSB 2019 proceedings",

publisher = "World Scientific",

address = "Singapore",

note = "Pacific Symposium on Biocomputing 2019 ; Conference date: 03-01-2019 Through 07-01-2019",

}

Gonzalez-Hernandez, G, Lu, Z, Leaman, R, Weissenbacher, D, Boland, MR, Chen, Y, Du, J, Fluck, J, Greene, CS, Holmes, J, Kashyap, A, Nielsen, RL, Ouyang, Z, Schaaf, S, Taroni, JN, Tao, C, Zhang, Y & Liu, H 2018, PSB 2019 Workshop on Text Mining and Visualization for Precision Medicine. in PSB 2019 proceedings. World Scientific, pp. 449-454, Pacific Symposium on Biocomputing 2019 , Fairmont Orchid, Big Island, Hawaii, United States, 03/01/2019. <https://psb.stanford.edu/psb-online/proceedings/psb19/>

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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

PY - 2018

Y1 - 2018

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 greatestchallenge 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 greatestchallenge 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.

M3 - Article in proceedings

SP - 449

EP - 454

BT - PSB 2019 proceedings

PB - World Scientific

T2 - Pacific Symposium on Biocomputing 2019

Y2 - 3 January 2019 through 7 January 2019

ER -

PSB 2019 Workshop on Text Mining and Visualization for Precision Medicine

Abstract

Conference

UN SDGs

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