Predicting conversion to psychosis using machine learning: response to Cannon.
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| Title: | Predicting conversion to psychosis using machine learning: response to Cannon. |
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| Authors: | Smucny J; Department of Psychiatry, University of California, Davis, Davis, CA, United States., Cannon TD; Department of Psychology, Yale University, New Haven, CT, United States.; Department of Psychiatry, Yale University, New Haven, CT, United States., Bearden CE; Department of Psychiatry, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.; Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States., Addington J; Department of Psychiatry, University of Calgary, Calgary, AB, Canada., Cadenhead KS; Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, United States., Cornblatt BA; Department of Psychiatry Research, Zucker Hillside Hospital, New York, NY, United States., Keshavan M; Department of Psychiatry, Harvard University, Cambridge, MA, United States., Mathalon DH; Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States., Perkins DO; Department of Psychiatry, University of San Diego, San Diego, CA, United States., Stone W; Department of Psychiatry, Harvard University, Cambridge, MA, United States., Walker EF; Department of Psychiatry, Emory University, Atlanta, GA, United States., Woods SW; Department of Psychology, Yale University, New Haven, CT, United States.; Department of Psychiatry, Yale University, New Haven, CT, United States., Davidson I; Department of Computer Science, University of California, Davis, Davis, CA, United States., Carter CS; Department of Psychiatry, University of California, Irvine, Irvine, CA, United States. |
| Source: | Frontiers in psychiatry [Front Psychiatry] 2025 Jan 15; Vol. 15, pp. 1520173. Date of Electronic Publication: 2025 Jan 15 (Print Publication: 2024). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101545006 Publication Model: eCollection Cited Medium: Print ISSN: 1664-0640 (Print) Linking ISSN: 16640640 NLM ISO Abbreviation: Front Psychiatry Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1664-0640 |
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| DOI: | 10.3389/fpsyt.2024.1520173 |
