| CPC A61B 5/4824 (2013.01) [G06F 3/015 (2013.01); G06F 18/2113 (2023.01); G06F 30/27 (2020.01); G06N 3/084 (2013.01)] | 9 Claims |

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1. A method implemented using one or more processors, comprising:
applying one or more simulation parameters to a digital twin created for a subject, wherein the digital twin simulates an anatomical structure of the subject, and wherein the one or more simulation parameters cause the digital twin to generate digital twin output that simulates behavior of the anatomical structure in response to the one or more simulation parameters;
comparing the generated digital twin output to one or more additional outputs of one or more healthy digital twins to determine at least one digital twin delta, wherein each of the one or more healthy digital twins simulates an anatomical structure in a different healthy subject;
applying data indicative of the digital twin output as input across a pain estimation machine learning model to generate pain estimation output, wherein the pain estimation machine learning model is trained to estimate a quantification of pain that the subject would experience based on application of the simulation parameters, and wherein the pain estimation output indicates the quantification of pain, and wherein the data indicative of the digital twin output comprises the at least one digital twin delta; and
based on the pain estimation output, rendering the quantification of pain using an output device or selecting a treatment plan.
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