Back to Search
Start Over
Machine learning-based discrimination of panic disorder from other anxiety disorders
- Source :
- Journal of Affective Disorders. 278:1-4
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- Backgrounds Panic disorder is a highly prevalent psychiatric disorder that substantially impairs quality of life and psychosocial function. Panic disorder arises from neurobiological substrates and developmental factors that distinguish it from other anxiety disorders. Differential diagnosis between panic disorder and other anxiety disorders has only been conducted in terms of a phenomenological spectrum. Methods Through a machine learning-based approach with heart rate variability (HRV) as input, we aimed to build algorithms that can differentiate panic disorder from other anxiety disorders. Five algorithms were used: random forest (RF), gradient boosting machine (GBM), support vector machine (SVM), artificial neural network (ANN), and regularized logistic regression (LR). 10-fold cross-validation with five repeats was used to build the final models. Results A total of 60 patients with panic disorder and 61 patients with other anxiety disorders (aged between 20 and 65 years) were recruited. The L1-regularized LR showed the best accuracy (0.784), followed by ANN (0.730), SVM (0.730), GBM (0.676), and finally RF (0.649). LR also had good performance in other measures, such as F1-score (0.790), specificity (0.737), sensitivity (0.833), and Matthews correlation coefficient (0.572). Limitations Cross-sectional design and limited sample size is limitations. Conclusion This study demonstrated that HRV can be used to differentiate panic disorder from other anxiety disorders. Future studies with larger sample sizes and longitudinal design are required to replicate the diagnostic utility of HRV in a machine learning approach.
- Subjects :
- Adult
Support Vector Machine
Machine learning
computer.software_genre
Logistic regression
Machine Learning
Young Adult
03 medical and health sciences
0302 clinical medicine
medicine
Humans
Heart rate variability
Aged
Artificial neural network
business.industry
Panic disorder
Middle Aged
medicine.disease
Anxiety Disorders
030227 psychiatry
Support vector machine
Psychiatry and Mental health
Clinical Psychology
Cross-Sectional Studies
Sample size determination
Quality of Life
Panic Disorder
Anxiety
Artificial intelligence
medicine.symptom
Psychology
business
computer
030217 neurology & neurosurgery
Anxiety disorder
Subjects
Details
- ISSN :
- 01650327
- Volume :
- 278
- Database :
- OpenAIRE
- Journal :
- Journal of Affective Disorders
- Accession number :
- edsair.doi.dedup.....d3f1eeb76d57e10d884bd9f5af504deb