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. 2022 Oct 26;56(6):5261–5315. doi: 10.1007/s10462-022-10304-3

Table 7.

List of XAI studies performing explanation consistency assessment

References # Cit. Application Input Data AI model(s) XAI method(s) Dataset(s)
Thimoteo et al. (2022) 2 COVID-19 diagnosis EHR SVM, RF SHAP COVID-19 Data Sharing/BR
Alves et al. (2021) 36 COVID-19 diagnosis EHR RF DTX, Criteria graph, LIME, SHAP COVID-19 datasetb
Okay et al. (2021) 1 Diabetes diagnosis EHR RF, GBDT SHAP, LIME Sylhet Diabetes dataset2
Oba et al. (2021) 1 Diabetes diagnosis EHR TabNet, XGBoost, LightGBM, CatBoost SHAP (all), attention (TabNet) Retrospective study
Elshawi et al. (2019) 132 Hypertension prediction EHR RF feature permutation, PDP, ICE, global surrogate models, LIME, SHAP Pilot study
Seedat et al. (2020) 1 Voice pathology assessment Audio features ExtraTrees SHAP,Morris sensitivity analysis Pilot study
Kapcia et al. (2021) 0 Lung cancer life expectancy prediction EHR RF LIME, SHAP Simulacrum dataset3
Duell et al. (2021) 9 Lung cancer mortality prediction EHR XGBoost LIME, SHAP, Anchors Simulacrum dataset
Moncada-Torres et al. (2021) 43 Breast cancer survival prediction EHR XGBoost SHAP Retrospective study
Ang et al. (2021) 0 ICU mortality risk prediction EHR RF, MLP SHAP MIMIC-III
Song et al. (2020) 33 AKI prediction EHR GBDT SHAP Retrospective study
Duckworth et al. (2021) 5 Hospital readmission prediction EHR XGBoost SHAP Retrospective study
Tahmassebi et al. (2020) 3 Eye state detection EEG XGBoost, DNN SHAP Pilot study
Antoniadi et al. (2021) 7 QoL assessment in ALS caregiving EHR XGBoost SHAP Retrospective study
Ward et al. (2021) 5 Pharmaco-vigilance monitoring EHR RF, XGBoost, ExtraTrees MDA, MDI, LIME, SHAP Retrospective study