Abstract
A growing body of evidence now suggests that precision psychiatry, an interdisciplinary field of psychiatry, precision medicine, and pharmacogenomics, serves as an indispensable foundation of medical practices by offering the accurate medication with the accurate dose at the accurate time to patients with psychiatric disorders. In light of the latest advancements in artificial intelligence and machine learning techniques, numerous biomarkers and genetic loci associated with psychiatric diseases and relevant treatments are being discovered in precision psychiatry research by employing neuroimaging and multi-omics. In this review, we focus on the latest developments for precision psychiatry research using artificial intelligence and machine learning approaches, such as deep learning and neural network algorithms, together with multi-omics and neuroimaging data. Firstly, we review precision psychiatry and pharmacogenomics studies that leverage various artificial intelligence and machine learning techniques to assess treatment prediction, prognosis prediction, diagnosis prediction, and the detection of potential biomarkers. In addition, we describe potential biomarkers and genetic loci that have been discovered to be associated with psychiatric diseases and relevant treatments. Moreover, we outline the limitations in regard to the previous precision psychiatry and pharmacogenomics studies. Finally, we present a discussion of directions and challenges for future research.
Highlights
Precision psychiatry, which is an emerging interdisciplinary field of psychiatry, precision medicine, and pharmacogenomics, is developing into essential practices in medicine with a promise of the individualization of clinical care for patients with psychiatric disorders
In the present review we showed some research reports to depict the related artificial intelligence and machine learning algorithms in the neurobiology of psychiatric disorders, it might be noted that precision psychiatry studies may be further improved by integrating the state-of-the-art artificial intelligence and machine learning frameworks with multi-omics and neuroimaging datasets [17]
In terms of neuroimaging-driven and multi-omics-driven techniques, it is of great interest that future prospective clinical trials concerning artificial intelligence and machine learning approaches to forecast medical outcomes and/or drug treatments may contribute to feasible explanations in public health as well as global health
Summary
Precision psychiatry, which is an emerging interdisciplinary field of psychiatry, precision medicine, and pharmacogenomics, is developing into essential practices in medicine with a promise of the individualization of clinical care for patients with psychiatric disorders. Sci. 2020, 21, 969 and disease status for patients with psychiatric disorders [6,17] To address this challenge, artificial intelligence and machine learning approaches may yield helpful software tools to achieve the promise of precision psychiatry by concerning specific biomarkers for drug treatments and disease status [6,17]. We show recent research studies in precision psychiatry and pharmacogenomics, which assessed disease status and drug treatments using artificial intelligence and machine learning approaches, such as deep learning and artificial neural network algorithms. In the context of artificial intelligence and machine learning methods, we provide various research studies with focus on four major categories including treatment prediction, prognosis prediction, diagnosis prediction, and the detection of potential biomarkers in terms of psychiatric disorders, precision psychiatry, and pharmacogenomics. While this review does not support the full set of related research studies reported in the literature, it describes a synthesis of those that can markedly influence public and population health-oriented applications in psychiatric disorders, precision psychiatry, and pharmacogenomics in the near to mid-term future
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
