Are We There Yet? Predicting Conversion to Psychosis Using Machine Learning / Jason Smucny en The American Journal of Psychiatry, Año 2023 - Vol. 180 - No. 11 (Noviembre)

Público ISBD [artículo]  inThe American Journal of Psychiatry > Año 2023 - Vol. 180 - No. 11 (Noviembre) . - pp. 836-840 Título : Are We There Yet? Predicting Conversion to Psychosis Using Machine Learning Tipo de documento: texto impreso Autores: Jason Smucny, Autor ; Ian Davidson, Autor ; Cameron S. Carter, Autor Fecha de publicación: 2024 Artículo en la página: pp. 836-840 Idioma : Inglés (eng) Idioma original : Inglés (eng) Palabras clave: Psicosis, Espectro de la esquizofrenia y otros trastornos psicóticos, Aprendizaje automático Resumen: The ability to accurately predict conversion to psychosis from clinical and other measurable features of an at-risk state is critically important to clinicians. To demonstrate clinical utility, these models should predict conversion with at least 80% sensitivity and specificity (1) with concurrently high positive and negative predictive value (PPV/NPV). Link: ./index.php?lvl=notice_display&id=31299 [artículo] Are We There Yet? Predicting Conversion to Psychosis Using Machine Learning [texto impreso] / Jason Smucny, Autor ; Ian Davidson, Autor ; Cameron S. Carter, Autor . - 2024 . - pp. 836-840. Idioma : Inglés (eng) Idioma original : Inglés (eng) in The American Journal of Psychiatry > Año 2023 - Vol. 180 - No. 11 (Noviembre) . - pp. 836-840 Palabras clave: Psicosis, Espectro de la esquizofrenia y otros trastornos psicóticos, Aprendizaje automático Resumen: The ability to accurately predict conversion to psychosis from clinical and other measurable features of an at-risk state is critically important to clinicians. To demonstrate clinical utility, these models should predict conversion with at least 80% sensitivity and specificity (1) with concurrently high positive and negative predictive value (PPV/NPV). Link: ./index.php?lvl=notice_display&id=31299

---

1 (1 - 1 / 1)