A commentary argues that algorithms flag arrhythmias but struggle with broader human context, using irregular heartbeat detection as an entry point. The piece emphasizes that recognizing meaningful health changes—such as psychosocial shifts and subtle behavioral patterns—requires human observation beyond sensor data. While not a clinical trial report, the framing matters to healthcare AI developers because it highlights the gap between physiological anomaly detection and holistic patient understanding. For product teams, it reinforces the need to pair signal analytics with workflows that can capture clinician or caregiver context. In practical terms, the article cautions against over-reliance on passive monitoring alone when outcomes depend on both physiological and behavioral indicators.