An author correction in npj Parkinson’s Disease renewed attention on a machine-learning approach designed to classify people with Parkinson’s disease who are at risk of falling. The publication’s indexed correction emphasizes the importance of accuracy in model features and evaluation when such tools are used to assess clinically meaningful risk. Fall risk remains a major clinical complication in Parkinson’s disease because it can occur without warning and drive downstream injuries and care utilization. The update adds momentum to the pipeline of ML-assisted screening and risk stratification approaches in movement disorders. For developers, the editorial action underscores how rapidly AI model papers must manage post-publication issues to preserve clinical interpretability and trust.