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Machine Learning in Neural Networks

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Frontiers in Psychiatry

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1192))

Abstract

Evidence now suggests that precision psychiatry is becoming a cornerstone of medical practices by providing the patient of psychiatric disorders with the right medication at the right dose at the right time. In light of recent advances in neuroimaging and multi-omics, more and more biomarkers associated with psychiatric diseases and treatment responses are being discovered in precision psychiatry applications by leveraging machine learning and neural network approaches. In this article, we focus on the most recent developments for research in precision psychiatry using machine learning, deep learning, and neural network algorithms, together with neuroimaging and multi-omics data. First, we describe different machine learning approaches that are employed to assess prediction for diagnosis, prognosis, and treatment in various precision psychiatry studies. We also survey probable biomarkers that have been identified to be involved in psychiatric diseases and treatment responses. Furthermore, we summarize the limitations with respect to the mentioned precision psychiatry studies. Finally, we address a discussion of future directions and challenges.

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Acknowledgements

This work was supported by grant MOST 107-2634-F-075-002 from Taiwan Ministry of Science and Technology, and grant V105D17-002-MY2-2 from the Taipei Veterans General Hospital. We thank Emily Ting for English editing.

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Authors and Affiliations

  1. Department of Electrical & Computer Engineering, University of Washington, Seattle, WA, 98195, USA

    Eugene Lin

  2. Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA

    Eugene Lin

  3. Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan

    Eugene Lin

  4. Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Shih-Pai Road, Sec. 2, 11217, Taipei, Taiwan

    Shih-Jen Tsai

  5. Division of Psychiatry, National Yang-Ming University, Taipei, Taiwan

    Shih-Jen Tsai

  6. Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan

    Shih-Jen Tsai

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  1. Eugene Lin
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  2. Shih-Jen Tsai
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Correspondence to Shih-Jen Tsai .

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Editors and Affiliations

  1. College of Medicine, Korea University, Seoul, Gyeonggi-do, Korea (Republic of)

    Yong-Ku Kim

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Lin, E., Tsai, SJ. (2019). Machine Learning in Neural Networks. In: Kim, YK. (eds) Frontiers in Psychiatry. Advances in Experimental Medicine and Biology, vol 1192. Springer, Singapore. https://doi.org/10.1007/978-981-32-9721-0_7

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