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AI and Big Data for Therapeutic Strategies in Psychiatry

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Trends of Artificial Intelligence and Big Data for E-Health

Part of the book series: Integrated Science ((IS,volume 9))

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Abstract

Psychiatric illnesses are well known in the research community through scientific findings in the past few decades. The detection and treatment of psychiatric diseases are unsatisfactory despite significant advancements in research. Current methods for diagnosing psychiatric diseases are purely based on physician–patient questionnaires. In most cases, these questionnaires are inaccurate and cannot show reliable symptoms for a particular psychiatric disorder. Everybody recognizes this era as an ‘era of big data’. Nobody is unable to explain how big data are big data. In this digital age, a huge amount of data is generated every second in relation to human behavior, such as body gestures, messages from social media networks, non-human data such as weather, and global positioning system signals. In this chapter, we discuss the applicability of the artificial intelligence technique for recognizing psychiatric disorders. Brief introduction to the datasets and tools available in the literature. Finally, we explore the challenges and limitations of these technologies in future research directions.

There is hope, even when your brain tells you there isn’t. John Green.

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Author information

Authors and Affiliations

  1. Machine Intelligence Research Labs, Berkeley, USA

    Shankru Guggari

  2. School of Computer Science and Engineering, KLE Technological University, Hubballi, India

    Shankru Guggari

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  1. Shankru Guggari
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Editor information

Editors and Affiliations

  1. National School of Computer Science (ENSI), Manouba University, COSMOS Laboratory, Manouba, Tunisia

    Houneida Sakly

  2. Department of Radiology, Stanford University, Palo Alto, CA, USA

    Kristen Yeom

  3. Northwestern University, Chicago, IL, USA

    Safwan Halabi

  4. Radiologist and Associate Professor in medical Imaging, Carthage Medical International Center Monastir and Sousse Medina Medical Imaging Center, Monastir, Tunisia

    Mourad Said

  5. Department Radiology, Stanford Medicine, Palo Alto, CA, USA

    Jayne Seekins

  6. National School of Computer Science (ENSI), Manouba University, COSMOS Laboratory, Manouba, Tunisia

    Moncef Tagina

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Guggari, S. (2022). AI and Big Data for Therapeutic Strategies in Psychiatry. In: Sakly, H., Yeom, K., Halabi, S., Said, M., Seekins, J., Tagina, M. (eds) Trends of Artificial Intelligence and Big Data for E-Health. Integrated Science, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-031-11199-0_9

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