The study explores whether machine learning (ML) algorithms can differentiate between anorexia nervosa (AN) and atypical anorexia nervosa (atypical AN) by analyzing various features while excluding BMI.
Results showed that ML classifiers performed well when BMI was included (about 75% accuracy) but significantly less effectively without it (just over 59% accuracy).
The findings suggest that BMI is critical for distinguishing between AN and atypical AN, prompting a reconsideration of the diagnostic criteria for atypical AN as it shares many characteristics with AN.
Long COVID has impacted 13.5% of Veterans in the VA Healthcare System, with a significant need for tailored mental health interventions to improve their recovery.
This study aims to assess a new recovery-oriented intervention called Long COVID Coping and Recovery (LCCR), designed specifically for Veterans, through a pilot program involving 18 participants over two years.
If successful in terms of feasibility and acceptability, the LCCR will be developed into a manualized version for wider testing to evaluate its effectiveness in improving symptoms and quality of life among Veterans with Long COVID.