Machine learning using random forest to differentiate between blow and fall situations of head trauma.

Blunt head trauma is a common occurrence in forensic practice. Interpreting the origin of craniocerebral injuries can be a challenging process, particularly when it comes to distinguishing between falls or inflicted blows. The objective of this study was to develop a predictive model using an innovative Random Forest (RF) classification approach to differentiate injuries caused by falls from those caused by blows.