Machine learning in mental health: a scoping review of methods and applications
BackgroundThis paper aims to synthesise the literature on machine learning (ML) and big
data applications for mental health, highlighting current research and applications in …
data applications for mental health, highlighting current research and applications in …
A review of using machine learning approaches for precision education
H Luan, CC Tsai - Educational Technology & Society, 2021 - JSTOR
In recent years, in the field of education, there has been a clear progressive trend toward
precision education. As a rapidly evolving AI technique, machine learning is viewed as an …
precision education. As a rapidly evolving AI technique, machine learning is viewed as an …
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 …
Prediction models of functional outcomes for individuals in the clinical high-risk state for psychosis or with recent-onset depression: a multimodal, multisite machine …
N Koutsouleris, L Kambeitz-Ilankovic… - JAMA …, 2018 - jamanetwork.com
Importance Social and occupational impairments contribute to the burden of psychosis and
depression. There is a need for risk stratification tools to inform personalized functional …
depression. There is a need for risk stratification tools to inform personalized functional …
The WPA-lancet psychiatry commission on the future of psychiatry
Background This Commission addresses several priority areas for psychiatry over the next
decade, and into the 21st century. These represent challenges and opportunities for the …
decade, and into the 21st century. These represent challenges and opportunities for the …
[HTML][HTML] Clinical prediction models in psychiatry: a systematic review of two decades of progress and challenges
Recent years have seen the rapid proliferation of clinical prediction models aiming to
support risk stratification and individualized care within psychiatry. Despite growing interest …
support risk stratification and individualized care within psychiatry. Despite growing interest …
Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, developing drugs for central nervous system (CNS) disorders remains the most …
However, developing drugs for central nervous system (CNS) disorders remains the most …
A scoping review of machine learning in psychotherapy research
Abstract Machine learning (ML) offers robust statistical and probabilistic techniques that can
help to make sense of large amounts of data. This scoping review paper aims to broadly …
help to make sense of large amounts of data. This scoping review paper aims to broadly …
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 …
[HTML][HTML] Childhood trauma in schizophrenia: current findings and research perspectives
Schizophrenia is a severe neuropsychiatric disorder with persistence of symptoms
throughout adult life in most of the affected patients. This unfavorable course is associated …
throughout adult life in most of the affected patients. This unfavorable course is associated …