New sensors, technologies, data sources, and analytics have transformed the delivery of medical care in ambulances, emergency departments, observation units and, increasingly, in the burgeoning field of 'home hospital' treatment. Clinical decisions are increasingly based upon algorithms which may be derived from biased datasets. This minitrack focuses on research and practice at the intersection of technology and acute medical care, machine learning in emergency medical environments, and the healthcare impact of bias in algorithmic medicine.