This paper presents a recommender system for teams of medical professionals working collaboratively in hospital operating rooms. The system recommends relevant virtual actions, such as retrieval of information resources and initiation of communication with professionals outside the operating rooms. Recommendations are based on the current state of the ongoing operation as recognised from sensor data using machine learning techniques. The selection and non-selection of virtual actions during operations are interpreted as implicit feedback and used to update the weight matrices that guide recommendations. A pilot user study involving medical professionals indicates that the adaptation mechanism is effective and that the system provides adequate recommendations.