A clinical study describes an AI model designed to forecast ICU vital signs and flag kidney injury earlier than conventional monitoring timelines. Using Temporal Fusion Transformer-style time-series architecture, the work highlights how handling multiple data streams with different sampling rhythms can improve earlier clinical event detection from routinely collected signals.