Machine learning
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Machine learning improves ADI-R efficiency
Early interventions in autism spectrum disorder (ASD) are essential to improve communication and behavioural skills in affected children. Now, researchers have used machine learning to derive new instrument algorithms that may help practitioners screen for autism more efficiently and effectively.
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Machine learning approach predicts suicide risk
A study has evaluated the performance of machine learning on routinely collected electronic health records, as a possible approach to accurately screen and detect adolescents at risk of making suicide attempts.
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Self-Harm & Suicide Issue – Foreword from the Editor
As a clinician, it certainly does feel that more and more young people are being referred, following self harm or with suicidal ideas, to the CAMHS service I work in. This nationwide increase in numbers is acknowledged in recent government reports, which are summarised in this edition.
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JCPP Editorial: Volume 56, Issue 10, October 2015
“Painting by numbers: using modern approaches to analyse and visualise clinical and research data” by David Coghill
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