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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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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DOI: https://doi.org/10.1007/978-981-10-8168-2_3
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