Random Forests for Hearing Disorder Diagnosis
Key Takeaways Item Response Theory (IRT) and Random Forest (RF) machine learning perform equally well for diagnostic classification when test items function the same across all patient groups. When test items show bias (Differential Item Functioning), IRT classification accuracy drops, while RF remains stable. RF offers a robust alternative for diagnosing conditions like tinnitus or…
