Identifying biological markers for improved precision medicine in psychiatry
EB Quinlan, T Banaschewski, GJ Barker… - Molecular …, 2020 - nature.com
Mental disorders represent an increasing personal and financial burden and yet treatment
development has stagnated in recent decades. Current disease classifications do not reflect …
development has stagnated in recent decades. Current disease classifications do not reflect …
Reflection impulsivity in binge drinking: behavioural and volumetric correlates
The degree to which an individual accumulates evidence prior to making a decision, also
known as reflection impulsivity, can be affected in psychiatric disorders. Here, we study …
known as reflection impulsivity, can be affected in psychiatric disorders. Here, we study …
Adolescent alcohol use is linked to disruptions in age-appropriate cortical thinning: an unsupervised machine learning approach
Cortical thickness changes dramatically during development and is associated with
adolescent drinking. However, previous findings have been inconsistent and limited by …
adolescent drinking. However, previous findings have been inconsistent and limited by …
Which adolescents develop persistent substance dependence in adulthood? Using population-representative longitudinal data to inform universal risk assessment
BackgroundTo our knowledge, there are no universal screening tools for substance
dependence that (1) were developed using a population-based sample,(2) estimate total …
dependence that (1) were developed using a population-based sample,(2) estimate total …
Utility of machine-learning approaches to identify behavioral markers for substance use disorders: impulsivity dimensions as predictors of current cocaine dependence
Background Identifying objective and accurate markers of cocaine dependence (CD) can
innovate its prevention and treatment. Existing evidence suggests that CD is characterized …
innovate its prevention and treatment. Existing evidence suggests that CD is characterized …
The biological classification of mental disorders (BeCOME) study: a protocol for an observational deep-phenotyping study for the identification of biological subtypes
TM Brückl, VI Spoormaker, PG Sämann, AK Brem… - BMC psychiatry, 2020 - Springer
Background A major research finding in the field of Biological Psychiatry is that symptom-
based categories of mental disorders map poorly onto dysfunctions in brain circuits or …
based categories of mental disorders map poorly onto dysfunctions in brain circuits or …
Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research
By promising more accurate diagnostics and individual treatment recommendations, deep
neural networks and in particular convolutional neural networks have advanced to a …
neural networks and in particular convolutional neural networks have advanced to a …
Psychiatric neural networks and precision therapeutics by machine learning
H Komatsu, E Watanabe, M Fukuchi - Biomedicines, 2021 - mdpi.com
Learning and environmental adaptation increase the likelihood of survival and improve the
quality of life. However, it is often difficult to judge optimal behaviors in real life due to highly …
quality of life. However, it is often difficult to judge optimal behaviors in real life due to highly …
Hunting for what works: Adolescents in addiction treatment
JA Silvers, LM Squeglia… - Alcoholism: Clinical …, 2019 - Wiley Online Library
Although adolescents are developmentally distinct from adults, they often receive addiction
treatment based on adult models. This is problematic because adolescents face significantly …
treatment based on adult models. This is problematic because adolescents face significantly …
Psychological and neural contributions to appetite self‐regulation
Objective This paper reviews the state of the science on psychological and neural
contributions to appetite self‐regulation in the context of obesity. Methods Three content …
contributions to appetite self‐regulation in the context of obesity. Methods Three content …