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A Roadmap for the Development of Applied Computational Psychiatry.

Type of publication Peer-reviewed
Publikationsform Review article (peer-reviewed)
Author Paulus Martin P, Huys Quentin J M, Maia Tiago V,
Project Neurobehavioural predictors of depression relapse
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Review article (peer-reviewed)

Journal Biological psychiatry: CNNI
Volume (Issue) 1
Page(s) 386 - 392
Title of proceedings Biological psychiatry: CNNI
DOI 10.1016/j.bpsc.2016.05.001

Abstract

Computational psychiatry is a burgeoning field that utilizes mathematical approaches to investigate psychiatric disorders, derive quantitative predictions, and integrate data across multiple levels of description. Computational psychiatry has already led to many new insights into the neurobehavioral mechanisms that underlie several psychiatric disorders, but its usefulness from a clinical standpoint is only now starting to be considered. Examples of computational psychiatry are highlighted, and a phase-based pipeline for the development of clinical computational-psychiatry applications is proposed, similar to the phase-based pipeline used in drug development. It is proposed that each phase has unique endpoints and deliverables, which will be important milestones to move tasks, procedures, computational models, and algorithms from the laboratory to clinical practice. Application of computational approaches should be tested on healthy volunteers in Phase I, transitioned to target populations in Phase IB and Phase IIA, and thoroughly evaluated using randomized clinical trials in Phase IIB and Phase III. Successful completion of these phases should be the basis of determining whether computational models are useful tools for prognosis, diagnosis, or treatment of psychiatric patients. A new type of infrastructure will be necessary to implement the proposed pipeline. This infrastructure should consist of groups of investigators with diverse backgrounds collaborating to make computational psychiatry relevant for the clinic.
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