Abstract: A system for optimizing resource allocation includes and/or interfaces with: a set of contextual data sources; a decision-making subsystem; and a set of schedules. Additionally or alternatively, the system can optionally include and/or interface with a set of user interfaces, memory, a set of data collection, and/or any other suitable components. A method for resource optimization includes: receiving a set of inputs; and processing the set of inputs and/or contextual data with a set of models to produce a set of schedules. Additionally or alternatively, the method can include any or all of: training the set of models; pre-processing the set of inputs to supplement the set of contextual data; dynamically adjusting the set of schedules; triggering a set of actions based on the set of schedules; updating the set of models; and/or any other processes.

Abstract: A system for optimizing resource allocation includes and/or interfaces with: a set of contextual data sources; a decision-making subsystem; and a set of schedules. Additionally or alternatively, the system can optionally include and/or interface with a set of user interfaces, memory, a set of data collection, and/or any other suitable components. A method for resource optimization includes: receiving a set of inputs; and processing the set of inputs and/or contextual data with a set of models to produce a set of schedules. Additionally or alternatively, the method can include any or all of: training the set of models; pre-processing the set of inputs to supplement the set of contextual data; dynamically adjusting the set of schedules; triggering a set of actions based on the set of schedules; updating the set of models; and/or any other processes.

Abstract: A system for optimizing resource allocation includes and/or interfaces with: a set of contextual data sources; a decision-making subsystem; and a set of schedules. Additionally or alternatively, the system can optionally include and/or interface with a set of user interfaces, memory, a set of data collection, and/or any other suitable components. A method for resource optimization includes: receiving a set of inputs; and processing the set of inputs and/or contextual data with a set of models to produce a set of schedules. Additionally or alternatively, the method can include any or all of: training the set of models; pre-processing the set of inputs to supplement the set of contextual data; dynamically adjusting the set of schedules; triggering a set of actions based on the set of schedules; updating the set of models; and/or any other processes.

Abstract: A system for optimizing resource allocation includes and/or interfaces with: a set of contextual data sources; a decision-making subsystem; and a set of schedules. Additionally or alternatively, the system can optionally include and/or interface with a set of user interfaces, memory, a set of data collection, and/or any other suitable components. A method for resource optimization includes: receiving a set of inputs; and processing the set of inputs and/or contextual data with a set of models to produce a set of schedules. Additionally or alternatively, the method can include any or all of: training the set of models; pre-processing the set of inputs to supplement the set of contextual data; dynamically adjusting the set of schedules; triggering a set of actions based on the set of schedules; updating the set of models; and/or any other processes.

Abstract: A system for optimizing resource allocation includes and/or interfaces with: a set of contextual data sources; a decision-making subsystem; and a set of schedules. Additionally or alternatively, the system can optionally include and/or interface with a set of user interfaces, memory, a set of data collection, and/or any other suitable components. A method for resource optimization includes: receiving a set of inputs; and processing the set of inputs and/or contextual data with a set of models to produce a set of schedules. Additionally or alternatively, the method can include any or all of: training the set of models; pre-processing the set of inputs to supplement the set of contextual data; dynamically adjusting the set of schedules; triggering a set of actions based on the set of schedules; updating the set of models; and/or any other processes.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Patient radiation exposure during computerized tomography (CT) scans is estimated. More specifically, efficient approaches for generating a suitable patient model which may be used to make an estimate of a radiation dose received at specific anatomical landmarks or organs of the patient are provided. Further disclosed are approaches for estimating the patient dose by interpolating the results of multiple simulations, and for enabling a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Patient radiation exposure during computerized tomography (CT) scans is estimated. More specifically, efficient approaches for generating a suitable patient model which may be used for estimating the radiation dose absorbed by a patient receiving a CT scan, for estimating a patient dose by interpolating the results of multiple simulations, and for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Patient radiation exposure during computerized tomography (CT) scans is estimated. More specifically, efficient approaches for generating a suitable patient model which may be used for estimating the radiation dose absorbed by a patient receiving a CT scan, for estimating a patient dose by interpolating the results of multiple simulations, and for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.

Abstract: Techniques are disclosed for estimating patient radiation exposure during computerized tomography (CT) scans. More specifically, embodiments of the invention provide efficient approaches for generating a suitable patient model used to make such an estimate, to approaches for estimating patient dose by interpolating the results of multiple simulations, and to approaches for a service provider to host a dose estimation service made available to multiple CT scan providers.