Machine learning prediction of anxiety symptoms in social anxiety disorder
Utilizing multimodal data from virtual reality sessions
Datos Bibliográficos
| ID | 15524643 |
|---|---|
| Autores | Jinhyun Park (0000-0002-5823-1106, Korea University), Jin-Hyun Park, Yu-Bin Shin, Yu‐Bin Shin (0000-0002-7311-9438, Korea University), Dooyoung Jung (0000-0002-5381-4847, Ulsan National Institute of Science and Technology), Ji-Won Hur, Ji‐Won Hur (0000-0002-1939-7365, Korea University), Seung Pil Pack (0000-0002-4874-0265, Korea University), Heon‐Jeong Lee (0000-0002-9560-2383, Korea University, autor de correspondencia), Heon-Jeong Lee, Hwamin Lee (Korea University, autor de correspondencia), Chul-Hyun Cho (0000-0003-0252-8741), Chul‐Hyun Cho (0000-0002-1663-9680, Korea University, autor de correspondencia) |
| Año | 2025 |
| Volumen | 15 |
| Páginas | 1504190-1504190 |
| Fecha de publicación | 2025-01-07 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Frontiers in Psychiatry (JOURNAL) |
| Identificadores de la revista | ISSN: 1664-0640 • E-ISSN: 1664-0640 |
| Editorial | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyt.2024.1504190 |
| PMID | 39896993 |
| OpenAlex | W4406146273 |
| Idioma | EN |
| Citas recibidas | 3 |
| Referencias citadas | 72 |
This study showed that a ML algorithm using integrated multimodal data can predict upper tertile anxiety symptoms in patients with SAD with higher performance than acoustic or physiological data obtained during a VR session. The results of this study can be used as evidence for personalized VR sessions and to demonstrate the strength of the clinical use of multimodal data
Anxiety · Cognitive psychology · Machine learning · Psychiatry · Social anxiety · Virtual reality · Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes · Clinical Psychology · Computer Science · Digital Mental Health Interventions · Mental Health Research Topics · Psychology · Artificial Intelligence
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| Obras citantes distintas | 3 |
|---|---|
| Citas por año | 3 |
| Intervalo de citas | 2025 - 2026 (2) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 3 |