Vinita Thakur, Olatunji Anthony Akerele, Edward Randell
Lean and Six Sigma as continuous quality improvement frameworks in the clinical diagnostic laboratory
Critical reviews in clinical laboratory sciences
machine learning ml models widely employed crash severity modelling yet interpretability remains underexplored interpretation crucial comprehending ml results aiding informed decisionmaking study aims implement interpretable ml visualize impacts factors crash severity using 5 years freeways data iran methods including classification regression trees cart knearest neighbours knns random forest rf artificial neural network ann support vector machines svm applied rf demonstrating superior accuracy recall f1score roc accumulated local effects ale utilized interpretation findings suggest light traffic conditions volumecapacity05 critical values around 005 038 higher proportion large trucks buses particularly 10 4 associated severe crashes additionally speeds exceeding 90 kmh drivers younger 30 years rollover crashes collisions fixed objects barriers nighttime driving driver fatigue elevate likelihood severe crashes