Table 1.

Overview of state of the art.

Author	Model	Dataset Type	Dataset Repository	Results	Year
Tajbakhsh et al. [21]	CNN	CTPA	Private dataset + PE challenge	Sensitivity: 0.83	2015
X-Yang et al. [10]	CNN	CTPA	Private dataset + PE challenge (2019)	Sensitivity 0.75	2019
Weifang Liu et al. [22]	D-L-CNN	CTPA	Private dataset	AUC: 0.926, Sensitivity: 0.94, Specificity: 0.76	2020
Shih-Cheng Huang et al. [7]	PENet.77-layer 3D CNN model	CTPA imaging	Private dataset	AUC: 0.85, Sensitivity: 0.75, Specificity: 0.80, Accuracy: 0.78	2020
Thomas Weikert et al. [23]	Deep-CNN	CTPA	Private dataset	Sensitivity: 0.92, Specificity: 0.95	2020
Aditya Mohan et al. [24]	Xception-CNN	CTPA	RSNA-PE challenge-(2020)	Accuracy: 0.90	2020
Deepta Rajan et al. [25]	2D U-Net	CTs	Private dataset	AUC: 0.94	2020
Tuomas Vainio et al. [26]	CNN	CTPA	Private dataset	AUC: 0.87	2021
Nahid ul Islam et al. [8]	SeResNextSe, ResNext50, SeXception, DenseNet121, ResNet18, ResNet50	CTPA	Kaggle-RSNA-PE-Challenge (2020)	AUC: 0.88, AUC: 0.89, AUC: 0.88, AUC: 0.88, AUC: 0.87, AUC: 0.86	2021
Sudhir Suman et al. [27]	CNN-LSTM	CTPA	Kaggle-RSNA-PE-Challenge (2020)	AUC: 0.95	2021
Ryan Schmid et al. [28]	D-L-algorithm	CTs	Private dataset	AUC: 0.79 Specificity: 0.99. Specificity: 0.99	2021