Table 2.

Summary for the input data types, evaluation metrics, training time, and optimizers in PINNs.

Characteristics	Details
Data type	In silico data
	In vivo data
	In vitro data
	Ex vivo data
Evaluation metrics	MSE (Mean squared error)
	AMSE (Averaged mean squared error)
	RMSE (Root mean squared error)
	MAE (Mean absolute error)
	MAPE (Mean absolute percent error) (Nazaret et al 2023)
	NRMSE (Normalized root mean squared error)
	RE (Relative error) (Xie and Yao 2022a, Isaev et al 2024a)
	ME (Mean error)
Training time	$131.29\mathrm{s}\sim 110\mathrm{h}$
Optimizer	Adam
	L-BFGS (Herrero et al 2022)
	Nadam (Tenderini et al 2022)