Machine learning-based computational validation of the Addictions Neuroclinical Assessment framework in relation to hazardous drinking.
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| Title: | Machine learning-based computational validation of the Addictions Neuroclinical Assessment framework in relation to hazardous drinking. |
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| Authors: | Elsayed M; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada.; Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, Canada., Belisario K; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada.; Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, Canada., Murphy J; Department of Psychology, University of Memphis, Memphis, USA., MacKillop J; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada.; Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, Canada. |
| Source: | Journal of psychiatry & neuroscience : JPN [J Psychiatry Neurosci] 2026 Jan 01; Vol. 51, pp. 1-11. |
| Publication Type: | Journal Article; Validation Study |
| Journal Info: | Publisher: Canadian Medical Association Country of Publication: Canada NLM ID: 9107859 Publication Model: Print Cited Medium: Internet ISSN: 1488-2434 (Electronic) Linking ISSN: 11804882 NLM ISO Abbreviation: J Psychiatry Neurosci Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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