Implementing precision psychiatry: a systematic review of individualized prediction models for clinical practice
G Salazar de Pablo, E Studerus… - Schizophrenia …, 2021 - academic.oup.com
Background The impact of precision psychiatry for clinical practice has not been
systematically appraised. This study aims to provide a comprehensive review of validated …
systematically appraised. This study aims to provide a comprehensive review of validated …
Machine learning in the prediction of depression treatment outcomes: a systematic review and meta-analysis
Background Multiple treatments are effective for major depressive disorder (MDD), but the
outcomes of each treatment vary broadly among individuals. Accurate prediction of …
outcomes of each treatment vary broadly among individuals. Accurate prediction of …
The promise of machine learning in predicting treatment outcomes in psychiatry
For many years, psychiatrists have tried to understand factors involved in response to
medications or psychotherapies, in order to personalize their treatment choices. There is …
medications or psychotherapies, in order to personalize their treatment choices. There is …
Reaching the end-game for GWAS: machine learning approaches for the prioritization of complex disease loci
Genome-wide association studies (GWAS) have revealed thousands of genetic loci that
underpin the complex biology of many human traits. However, the strength of GWAS–the …
underpin the complex biology of many human traits. However, the strength of GWAS–the …
A deep learning approach for predicting antidepressant response in major depression using clinical and genetic biomarkers
In the wake of recent advances in scientific research, personalized medicine using deep
learning techniques represents a new paradigm. In this work, our goal was to establish deep …
learning techniques represents a new paradigm. In this work, our goal was to establish deep …
Precision psychiatry applications with pharmacogenomics: artificial intelligence and machine learning approaches
A growing body of evidence now suggests that precision psychiatry, an interdisciplinary field
of psychiatry, precision medicine, and pharmacogenomics, serves as an indispensable …
of psychiatry, precision medicine, and pharmacogenomics, serves as an indispensable …
Challenges and future prospects of precision medicine in psychiatry
M Manchia, C Pisanu, A Squassina… - Pharmacogenomics …, 2020 - Taylor & Francis
Precision medicine is increasingly recognized as a promising approach to improve disease
treatment, taking into consideration the individual clinical and biological characteristics …
treatment, taking into consideration the individual clinical and biological characteristics …
Deep learning for the prediction of treatment response in depression
L Squarcina, FM Villa, M Nobile, E Grisan… - Journal of affective …, 2021 - Elsevier
Background Mood disorders are characterized by heterogeneity in severity, symptoms and
treatment response. The possibility of selecting the correct therapy on the basis of patient …
treatment response. The possibility of selecting the correct therapy on the basis of patient …
Cloud‐aided online EEG classification system for brain healthcare: A case study of depression evaluation with a lightweight CNN
Brain healthcare, when supported by Internet of Things, can perform online and accurate
analysis of brain big data for the classification of multivariate Electroencephalogram (EEG) …
analysis of brain big data for the classification of multivariate Electroencephalogram (EEG) …
Multi-omics driven predictions of response to acute phase combination antidepressant therapy: a machine learning approach with cross-trial replication
JB Joyce, CW Grant, D Liu… - Translational …, 2021 - nature.com
Combination antidepressant pharmacotherapies are frequently used to treat major
depressive disorder (MDD). However, there is no evidence that machine learning …
depressive disorder (MDD). However, there is no evidence that machine learning …