Detection and mitigation of radiation exposure in medical environments

A method, comprising:

• determining, by a first machine learning model based on a first input comprising data for a medical procedure performed in a medical environment, a first output identifying an object or a person at a first location in the medical environment, the data including one or more images captured by a sensor within the medical environment;
• determining, respective to a second location of a radiation-emitting device in a medical environment, one or more radiation metrics corresponding to propagation of radiation from the radiation-emitting device through the medical environment;
• and
• generating, by a second machine learning model based on a second input comprising the radiation metrics, the first location, and the first output, a second output indicative of a quantity of radiation exposure of the object or the person at the first location.

A non-transitory computer readable medium including one or more instructions stored thereon and executable by a processor to:

• determine, by the processor via a first machine learning model based on a first input comprising data for a medical procedure performed in a medical environment, a first output identifying an object or a person at a first location in the medical environment, the data including one or more images captured by a sensor within the medical environment;
• determine, the processor and respective to a second location of a radiation-emitting device in a medical environment, one or more radiation metrics corresponding to propagation of radiation from the radiation-emitting device through the medical environment;
• and
• generate, by the processor via a second machine learning model based on a second input comprising the radiation metrics, the first location, and the first output, a second output indicative of a quantity of radiation exposure of the object or the person at the first location.