Biblioteca Humberto Rosselli Quijano
[artículo]
| Título : |
Easy and low-cost identification of metabolic syndrome in patients treated with second-generation antipsychotics : artificial neural network and logistic regression models |
| Tipo de documento: |
texto impreso |
| Autores: |
Chao Cheng Lin, Autor ; Ya-Mei Bai, Autor ; Jen Yeu Chen, Autor |
| Fecha de publicación: |
2022 |
| Artículo en la página: |
pp. 225-234 |
| Idioma : |
Inglés (eng) Idioma original : Inglés (eng) |
| Palabras clave: |
Antropometría, Antipsicóticos, Presión arterial, Síndrome metabólico, Redes Neuronales, Trastornos psicóticos, Esquizofrenia. |
| Resumen: |
Metabolic syndrome (MetS) is an important side effect of second-generation antipsychotics (SGAs). However, many SGA-treated patients with MetS remain undetected. In this study, we trained and validated artificial neural network (ANN) and multiple logistic regression models without biochemical parameters to rapidly identify MetS in patients with SGA treatment. |
| Link: |
./index.php?lvl=notice_display&id=28151 |
in The Journal of Clinical Psychiatry > Año 2010 - Vol. 71 - No. 3 (Marzo) . - pp. 225-234
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