Artificial intelligence for mental health care: clinical applications, barriers, facilitators, and artificial wisdom
Artificial intelligence (AI) is increasingly employed in health care fields such as oncology,
radiology, and dermatology. However, the use of AI in mental health care and …
radiology, and dermatology. However, the use of AI in mental health care and …
Annual research review: enduring neurobiological effects of childhood abuse and neglect
MH Teicher, JA Samson - Journal of child psychology and …, 2016 - Wiley Online Library
Background Childhood maltreatment is the most important preventable cause of
psychopathology accounting for about 45% of the population attributable risk for childhood …
psychopathology accounting for about 45% of the population attributable risk for childhood …
[HTML][HTML] Common and distinct patterns of intrinsic brain activity alterations in major depression and bipolar disorder: voxel-based meta-analysis
J Gong, J Wang, S Qiu, P Chen, Z Luo, J Wang… - Translational …, 2020 - nature.com
Identification of intrinsic brain activity differences and similarities between major depression
(MDD) and bipolar disorder (BD) is necessary. However, results have not yet yielded …
(MDD) and bipolar disorder (BD) is necessary. However, results have not yet yielded …
Machine learning in major depression: From classification to treatment outcome prediction
S Gao, VD Calhoun, J Sui - CNS neuroscience & therapeutics, 2018 - Wiley Online Library
Aims Major depression disorder (MDD) is the single greatest cause of disability and
morbidity, and affects about 10% of the population worldwide. Currently, there are no …
morbidity, and affects about 10% of the population worldwide. Currently, there are no …
[HTML][HTML] Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis
Finding robust brain substrates of mood disorders is an important target for research. The
degree to which major depression (MDD) and bipolar disorder (BD) are associated with …
degree to which major depression (MDD) and bipolar disorder (BD) are associated with …
Cross-disorder analysis of brain structural abnormalities in six major psychiatric disorders: a secondary analysis of mega-and meta-analytical findings from the …
N Opel, J Goltermann, M Hermesdorf, K Berger… - Biological …, 2020 - Elsevier
Background Neuroimaging studies have consistently reported similar brain structural
abnormalities across different psychiatric disorders. Yet, the extent and regional distribution …
abnormalities across different psychiatric disorders. Yet, the extent and regional distribution …
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 …
Towards a brain‐based predictome of mental illness
Neuroimaging‐based approaches have been extensively applied to study mental illness in
recent years and have deepened our understanding of both cognitively healthy and …
recent years and have deepened our understanding of both cognitively healthy and …
[HTML][HTML] From estimating activation locality to predicting disorder: a review of pattern recognition for neuroimaging-based psychiatric diagnostics
Psychiatric disorders are increasingly being recognised as having a biological basis, but
their diagnosis is made exclusively behaviourally. A promising approach for …
their diagnosis is made exclusively behaviourally. A promising approach for …
Machine learning approaches for clinical psychology and psychiatry
Machine learning approaches for clinical psychology and psychiatry explicitly focus on
learning statistical functions from multidimensional data sets to make generalizable …
learning statistical functions from multidimensional data sets to make generalizable …