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 and method for optimizing radiological workflow management and medical image review is disclosed. A preferred embodiment provides a system interoperable with various RIS and PACS systems and that provides efficient access to information, a dynamic prioritized worklist that constantly changes to address optimize distribution of studies and timely review. The novel system facilitates automated assignment, communication between physicians, technicians and radiologists regarding orders, radiographs, reports and studies. The system analyzes exam data, urgency and pendency times, among other things, to automatically determine an overall priority for each case. Cases are assigned for review in the most efficient time, resulting in optimal turnaround time and improved patient care.

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 100 for automatically generating a field of a radiology report includes a set of one or more models. A method for automatically generating a field of a radiology report includes: receiving a radiologist identifier (radiologist ID); receiving a set of finding inputs; determining a context of each of the set of finding inputs; determining text associated with a portion or all of the radiology report based on the context and the radiologist style; and inserting the text into the report.

Abstract: A system and method for optimizing radiological workflow management and medical image review is disclosed. A preferred embodiment provides a system interoperable with various RIS and PACS systems and that provides efficient access to information, a dynamic prioritized worklist that constantly changes to address optimize distribution of studies and timely review. The novel system facilitates automated assignment, communication between physicians, technicians and radiologists regarding orders, radiographs, reports and studies. The system analyzes exam data, urgency and pendency times, among other things, to automatically determine an overall priority for each case. Cases are assigned for review in the most efficient time, resulting in optimal turnaround time and improved patient care.

Abstract: A system 100 for automatically generating a field of a radiology report includes a set of one or more models. A method for automatically generating a field of a radiology report includes: receiving a radiologist identifier (radiologist ID); receiving a set of finding inputs; determining a context of each of the set of finding inputs; determining text associated with a portion or all of the radiology report based on the context and the radiologist style; and inserting the text into the report.

Abstract: A system 100 for automatically generating a field of a radiology report includes a set of one or more models. A method for automatically generating a field of a radiology report includes: receiving a radiologist identifier (radiologist ID); receiving a set of finding inputs; determining a context of each of the set of finding inputs; determining text associated with a portion or all of the radiology report based on the context and the radiologist style; and inserting the text into the report.

Abstract: A system 100 for automatically generating a field of a radiology report includes a set of one or more models. A method for automatically generating a field of a radiology report includes: receiving a radiologist identifier (radiologist ID); receiving a set of finding inputs; determining a context of each of the set of finding inputs; determining text associated with a portion or all of the radiology report based on the context and the radiologist style; and inserting the text into the report.

Abstract: A method for the computer-assisted implementation of radiology recommendations includes any or all of: receiving a set of inputs; determining and/or identifying a set of findings; determining a set of follow-up recommendations; and triggering a set of outputs and/or actions based on the set of follow-up recommendations. A system for the computer-assisted implementation of radiology recommendations preferably includes and/or interfaces a set of computing subsystems and/or processing subsystems, but can additionally include and/or interface with a set of devices (e.g., user devices), models, and/or any other components.

Abstract: A method for the automated annotation of radiology findings includes: receiving a set of inputs, determining a set of outputs based on the set of inputs, assigning labels to the set of inputs, and annotating the set of inputs based on the labels. Additionally, the method can include any or all of: presenting annotated inputs to a user, comparing multiple sets of inputs, transmitting a set of outputs to a radiologist report, or any other suitable processes.

Abstract: A system 100 for automatically generating a field of a radiology report includes a set of one or more models. A method for automatically generating a field of a radiology report includes: receiving a radiologist identifier (radiologist ID); receiving a set of finding inputs; determining a context of each of the set of finding inputs; determining text associated with a portion or all of the radiology report based on the context and the radiologist style; and inserting the text into the report.