Simulation-based surgical procedure planning system
A computing device for generating a surgical procedure plan via surgical simulation may include a processor. The processor may be configured to obtain an indication of a surgical task. The surgical task may be associated with a surgical step of the surgical procedure plan. The processor may be configured to obtain a surgical choice and a corresponding predicted surgical outcome. The surgical choice and the corresponding predicted surgical outcome may be associated with the surgical task. The processor may be configured to generate a visualization of the surgical choice and the corresponding predicted surgical outcome in a simulated environment. The processor may be configured to obtain an indication of the surgical choice being selected. The processor may be configured to store the surgical choice in the surgical procedure plan.
1 . A computing device for generating a surgical procedure plan via surgical simulation, the computing device comprising:
a processor configured to:
obtain an indication of a surgical task, wherein the surgical task is associated with a surgical step of the surgical procedure plan;
obtain a surgical choice, wherein the surgical choice is associated with the surgical task;
determine a surgeon-based tool-tissue simulation that avoids a surgical error, wherein the surgeon-based tool-tissue simulation is based on the surgical choice, a surgical experience level, and a surgical workload;
determine an infection exposure simulation for a room layout;
determine a predicted surgical outcome based on the surgeon-based tool-tissue simulation, the infection exposure simulation, and a surgical setup data, wherein the surgical setup data comprises the room layout, a staff layout, and a patient position, wherein the patient position minimizes injury to a patient, and wherein the staff layout indicates at least a location of a staff member;
generate a visualization of the surgical choice and the predicted surgical outcome using a simulated environment;
obtain an indication confirming the surgical choice as being selected; and
store the surgical choice in the surgical procedure plan.
2 . The computing device of claim 1 , wherein the indication of the surgical task is obtained from a surgical procedure planning user interface.
3 . The computing device of claim 1 , wherein the indication of the surgical task comprises identifying information of the surgical procedure plan, identifying information of the surgical task, and identifying information of the surgical step.
4 . The computing device of claim 1 , wherein the surgical task comprises a task that contributes to a completion of the surgical step of the surgical procedure plan.
5 . The computing device of claim 1 , wherein the processor is further configured to train a machine learning (ML) model using data from at least a surgical procedure.
6 . The computing device of claim 1 , wherein the surgical choice is a first surgical choice, wherein the predicted surgical outcome is a first corresponding predicted surgical outcome, wherein the visualization is a first visualization, and wherein the processor is further configured to:
obtain a second surgical choice, wherein the second surgical choice is associated with the surgical task;
determine a second predicted surgical outcome based on the second surgical choice and the surgical setup data; and
generate a second visualization of the second surgical choice and the second predicted surgical outcome in the simulated environment.
7 . The computing device of claim 1 , wherein the processor is further configured to determine a machine learning (ML) model, wherein the ML model is associated with data from at least a surgical procedure.
8 . The computing device of claim 7 , wherein the processor being configured to determine the predicted surgical outcome further comprises the processor being configured to determine the predicted surgical outcome based on the surgeon-based tool-tissue simulation, the infection exposure simulation, the surgical setup data, and the ML model.
9 . A computer-implemented method for generating a surgical procedure plan via surgical simulation, the method comprising:
obtaining an indication of a surgical task, wherein the surgical task is associated with a surgical step of the surgical procedure plan;
obtaining a surgical choice, wherein the surgical choice is associated with the surgical task;
determining a surgeon-based tool-tissue simulation that avoids a surgical error, wherein the surgeon-based tool-tissue simulation is based on the surgical choice, a surgical experience level, and a surgical workload;
determining an infection exposure simulation for a room layout;
determining a predicted surgical outcome based on the surgeon-based tool-tissue simulation, the infection exposure simulation, and a surgical setup data, wherein the surgical setup data comprises the room layout, a staff layout, and a patient position, wherein the patient position minimizes injury to a patient, and wherein the staff layout indicates at least a location of a staff member;
generating a visualization of the surgical choice and the predicted surgical outcome using a simulated environment;
obtaining an indication confirming the surgical choice as being selected; and
storing the surgical choice in the surgical procedure plan.
10 . The computer-implemented method of claim 9 , wherein the indication of the surgical task is obtained from a surgical procedure planning user interface.
11 . The computer-implemented method of claim 9 , wherein the indication of the surgical task comprises identifying information of the surgical procedure plan, identifying information of the surgical task, and identifying information of the surgical step.
12 . The computer-implemented method of claim 9 , wherein the surgical task comprises a task that contributes to a completion of the surgical step of the surgical procedure plan.
13 . The computer-implemented method of claim 9 , further comprising:
training a machine learning (ML) model using data from at least a surgical procedure.
14 . The computer-implemented method of claim 9 , wherein the surgical choice is a first surgical choice, wherein the predicted surgical outcome is a first corresponding predicted surgical outcome, wherein the visualization is a first visualization, and wherein the method further comprises:
obtaining a second surgical choice, wherein the second surgical choice is associated with the surgical task;
determining a second predicted surgical outcome based on the second surgical choice and the surgical setup data; and
generating a second visualization of the second surgical choice and the second predicted surgical outcome in the simulated environment.
15 . The computer-implemented method of claim 9 , wherein the method further comprises determining a machine learning (ML) model, wherein the ML model is associated with data from at least a surgical procedure.
16 . The computer-implemented method of claim 15 , wherein determining the predicted surgical outcome further comprises determining the predicted surgical outcome based on the surgeon-based tool-tissue simulation, the infection exposure simulation, the surgical setup data, and the ML model.