Employing Machine Learning For Enhanced Abdominal Fat Prediction In Cavitation Post-treatment

This article discusses the use of machine learning algorithms in predicting obesity and overweight, with a focus on improving early identification and risk assessment. The study was conducted as a clinical trial and adhered to ethical standards. A sample size calculation was performed to ensure a statistical power of 0.95. The results showed that a minimum sample size of 34 observations is needed for a 95% chance of correctly detecting obesity and overweight.