A JAMA study reports the YEARS diagnostic algorithm performs on par with standard CTPA imaging for suspected pulmonary embolism in cancer patients while reducing the number of patients who need invasive imaging. The report positions YEARS as a frontline decision tool for balancing diagnostic certainty and resource utilization. Elsewhere, KAIST researchers unveiled an at-home AI system for detecting early cerebrovascular disease signs using contactless sensor monitoring of behavioral and environmental patterns in older adults. The combination reflects two parallel moves in biopharma-linked care delivery: AI-assisted triage in acute settings and sensor-driven early detection approaches that could reduce downstream clinical burden.