ArticleGeneral psychiatry2020
Machine learning methods in psychiatry: a brief introduction.
Article in General psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Integrative metabolomics and machine learning identify biomarkers of adolescent social anxiety disorder.World journal of pediatrics : WJP · 2026Article
- Characterisation of intrusive memories and prediction from memory-related genes and cognitive and emotional factors.Scientific reports · 2025Article
- Can machine learning predict PTSD symptoms from trauma narratives of children and adolescents?European journal of psychotraumatology · 2025Article
- Artificial Intelligence and Bipolar Disorder: Applications of Machine Learning Models for Diagnosis, Treatment, and Outcome Prediction.Alpha psychiatry · 2025Article
- Is Artificial Intelligence the Next Co-Pilot for Primary Care in Diagnosing and Recommending Treatments for Depression?Medical sciences (Basel, Switzerland) · 2025Review
- Predicting adolescent psychopathology from early life factors: A machine learning tutorial.Global epidemiology · 2024Article
- Public perspectives on AI diagnosis of mental illness.General psychiatry · 2024Article
- Unipolar and Bipolar Depression Detection and Classification Based on Actigraphic Registration of Motor Activity Using Machine Learning and Uniform Manifold Approximation and Projection Methods.Diagnostics (Basel, Switzerland) · 2023Article
- Modern views of machine learning for precision psychiatry.Patterns (New York, N.Y.) · 2022Review
- Classification of Depressive and Schizophrenic Episodes Using Night-Time Motor Activity Signal.Healthcare (Basel, Switzerland) · 2022Article
- Identifying Methamphetamine Abstainers With Convolutional Neural Networks and Short-Time Fourier Transform.Frontiers in psychology · 2021Article
- Detecting Presence of PTSD Using Sentiment Analysis From Text Data.Frontiers in psychiatry · 2021Article
- Peripheral Biomarkers in DSM-5 Anxiety Disorders: An Updated Overview.Brain sciences · 2020Review
- Advanced machine learning methods in psychiatry: an introduction.General psychiatry · 2020Article
- Machine learning algorithms for suicide risk: a premature arms race?General psychiatry · 2020Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Machine learning (ML) techniques have been widely used to address mental health questions. We discuss two main aspects of ML in psychiatry in this paper, that is, supervised learning and unsupervised learning. Examples are used to illustrate how ML has been implemented in recent mental health research.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.