TERT and preeclampsia: Based on prior research, RF has demonstrated remarkable performance compared with other machine learning algorithms in various prediction tasks, such as predicting preeclampsia, in-hospital mortality for critically ill patients with sepsis-associated acute kidney injury, telomerase reverse transcriptase (TERT) promoter mutation status in adult glioblastoma, and meningioma grade (34–37).