Table 7.
Summary of the results for PINNs in the areas of neural dynamics, cancer, and electromyography.
| Article | Objective | Signal characteristics | Error metrics |
|---|---|---|---|
| Sun et al (2022) | Neural mass model | In silico data | Pearson correlation; Average localization error |
| Ferrante et al (2022) | Neural modeling | In silico data | MSE |
| Ottens et al (2022) | Pancreatic cancer | In silico data; Clinical dataset | NRMSE |
| Mukhmetov et al (2023) | Temperature prediction in cancerous breasts | In silico data | Relative L1-norm error |
| Perez-Raya and Kandlikar (2023) | Thermal modeling of breast cancer | In silico data | RE |
| Taneja et al (2022) | Motion prediction and parameter identification of human MSK systems | Surface electromyography data | MSE |
| Li et al (2022) | Muscle force decoding | Surface electromyography data | RMSE |
| Zhang et al (2022) | Ankle joint torque prediction | Surface electromyography data | NRMSE |
| Ma et al (2024) | Muscle force prediction | Surface electromyography data | RMSE |
Definitions of NRMSE, RMSE, MSE, and RE can be found in table 2.