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Possible Clinical Use of Big Data: Personal Brain Connectomics

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Proceedings of the Pacific Rim Statistical Conference for Production Engineering

Part of the book series: ICSA Book Series in Statistics ((ICSABSS))

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Abstract

The biggest data is brain imaging data, which waited for clinical use during the last three decades. Topographic data interpretation prevailed for the first two decades, and only during the last decade, connectivity or connectomics data began to be analyzed properly. Owing to topological data interpretation and timely introduction of likelihood method based on hierarchical generalized linear model, we now foresee the clinical use of personal connectomics for classification and prediction of disease prognosis for brain diseases without any clue by currently available diagnostic methods.

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Acknowledgements

This study was supported by the National Research Foundation of Korea (NRF) Grant funded by Korean Government (MOE) (No. 2016R1D1A1A02937497), the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIP) (No. 2015M3C7A1028926, No.2017R1A5A1015626 and No. 2017M3C7A1048079).

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Authors and Affiliations

  1. Department of Nuclear Medicine, Department of Molecular Medicine and Biopharmaceutical Sciences, College of Medicine, Seoul National University (SNU) and SNU Hospital, Seoul, Korea

    Dong Soo Lee

  2. Korean Brain Research Institute, Daegu, Korea

    Dong Soo Lee

Authors
  1. Dong Soo Lee
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Correspondence to Dong Soo Lee .

Editor information

Editors and Affiliations

  1. Oregon Health & Science University , Portland, Oregon, USA

    Dongseok Choi

  2. Pukyong National University , Busan, Korea (Republic of)

    Daeheung Jang

  3. Stanford University, Stanford, California, USA

    Tze Leung Lai

  4. Seoul National University, Gwanak-gu, Seoul, Korea (Republic of)

    Youngjo Lee

  5. Stanford University , Stanford, California, USA

    Ying Lu

  6. University of Michigan–Ann Arbor, Ann Arbor, Michigan, USA

    Jun Ni

  7. University of Wisconsin–Madison, Madison, Wisconsin, USA

    Peter Qian

  8. University of Florida, Gainesville, Florida, USA

    Peihua Qiu

  9. University of Chicago , Chicago, Illinois, USA

    George Tiao

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Lee, D.S. (2018). Possible Clinical Use of Big Data: Personal Brain Connectomics. In: Choi, D., et al. Proceedings of the Pacific Rim Statistical Conference for Production Engineering. ICSA Book Series in Statistics. Springer, Singapore. https://doi.org/10.1007/978-981-10-8168-2_3

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