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Mental Health Clinical Decision Support Exploiting Big Data

Mental Health Clinical Decision Support Exploiting Big Data
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Author(s): Jan Kalina (The Czech Academy of Sciences, Czech Republic)
Copyright: 2019
Pages: 25
Source title: Computational Methods and Algorithms for Medicine and Optimized Clinical Practice
Source Author(s)/Editor(s): Kwok Tai Chui (The Open University of Hong Kong, Hong Kong)and Miltiadis D. Lytras (Effat University, Saudi Arabia)
DOI: 10.4018/978-1-5225-8244-1.ch008

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Abstract

The complexity of clinical decision-making is immensely increasing with the advent of big data with a clinical relevance. Clinical decision systems represent useful e-health tools applicable to various tasks within the clinical decision-making process. This chapter is devoted to basic principles of clinical decision support systems and their benefits for healthcare and patient safety. Big data is crucial input for clinical decision support systems and is helpful in the task to find the diagnosis, prognosis, and therapy. Statistical challenges of analyzing big data in psychiatry are overviewed, with a particular interest for psychiatry. Various barriers preventing telemedicine tools from expanding to the field of mental health are discussed. The development of decision support systems is claimed here to play a key role in the development of information-based medicine, particularly in psychiatry. Information technology will be ultimately able to combine various information sources including big data to present and enforce a holistic information-based approach to psychiatric care.

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