Liu and coworkers have developed an XGBoost-based machine learning model employing radiomic features from brain MRI to distinguish primary brain tumors from lung cancer-derived brain metastases. This differentiation is pivotal for tailored treatment strategies and prognosis. The study demonstrates high accuracy and reliability, representing a leap forward in diagnostic radiology through advanced computational approaches.