Table 4 Multiple disease detection. The datasets, manifestations, assessment measures and results are shown in each column, respectively
From: Computer-aided detection in chest radiography based on artificial intelligence: a survey
Study | Datasets | Conditions | Measurements | Results |
|---|---|---|---|---|
Avni et al. [104] | Custom | Left and right pulmonary pleural effusion, cardiomegaly, and septum enlargement | AUC | Left and right pulmonary pleural effusion: 80%; cardiomegaly: 79.2%; septum enlargement: 88.2% |
Noor et al. [105] | Custom | Lobar pneumonia, tuberculosis, and lung cancer | Accuracy | 70%, 97%, and 79%, respectively |
Bar et al. [75] | Custom | Right pleural effusion, cardiomegaly, health, and abnormal disease | AUC | 93%, 89%, and 79%, respectively |
Cicero et al. [106] | Custom | Normal, cardiomegaly, pleural effusion, pulmonary edema, and pneumothorax | AUC | 96.4%, 87.5%, 85%, 96.2%, 86.8%, and 86.1%, respectively |
Wang et al. [23] | Chest-Xray14 | 14 common diseases in CXRs | AUC | Mean: 73.8% |
Yao et al. [107] | Chest-Xray14 | 14 common diseases in CXRs | AUC | Mean: 80.3%; however, limited training focuses on biased interdependence and cannot accurately represent the actual distribution of morbidities |
Rajpurkar et al. [13] | Chest-Xray14 | 14 common diseases in CXRs | AUC | Mean: 84.2%; pneumonia (76.8%) exceeded the human level |
Kumar et al. [109] | Chest-Xray14 | 14 common diseases in CXRs | AUC | Mean: 79.5%; cardiomegaly (91.33%) beyond the previous method |
Guan et al. [111] | Chest-Xray14 | 14 common diseases in CXRs | AUC | Mean: 87.1% |