Table 3.
Diagnosing COVID-19.
| Study; outcome | Highest-weighted features | ML approaches | Sample size (no. of positive cases) | Performance |
|---|---|---|---|---|
| Li et al. [46]; diagnosis of COVID-19 and discrimination between influenza and COVID-19 | Age, CT scan result, temperature, lymphocyte, fever, coughing | XGBoost | 413 patients (−) | Sensitivity of 92.5% and specificity of 97.9% |
| Kukar et al. [49]; diagnosis of COVID-19 | MCHC, eosinophils count, albumin, INR, prothrombin activity % | RF, DNN, and XGBoost (selected) | 5333 patients (160 positive) | AUC of 97%, sensitivity of 81.9%, specificity of 97.9% |
| Bayat et al. [48]; diagnosis of COVID-19 | Ferritin, WBC, eosinophil, temperature, CRP, LDH, D-dimer, basophil count, monocyte %, AST (in descending order of importance) | XGBoost | 75,991 patients (7335 positive) | Accuracy of 86.4%, specificity of 86.8%, sensitivity of 82.4% |
| Schwab et al. [95]; diagnosis of COVID-19 | MISSING arterial tactic acid, age, leukocyte count, platelets, creatinine | LR, NN, RF, SVM, and (XGBoost selected) | 5644 (556 positive) | XGBoost model achieved AUC of 0.66, sensitivity of 75%, and specificity of 49% |
| Wu et al. [50]; diagnosis of COVID-19 | Total bilirubin, glucose, creatinine, LDH, CK-MB, potassium, total protein, calcium, magnesium, PDW, basophils | RF | 253 samples from 169 suspected patients (105 samples from 27 patients confirmed positive) | AUC of 99.26%, a sensitivity of 100%, and a specificity of 94.44% with an independent test set |
| Brinati et al. [51]; diagnosis of COVID-19 | AST, lymphocytes, LDH, WBC, eosinophils, ALT, age | DT, ET, KNN, LR, NB, SVM, TWRF, and (RF selected) | 279 patients (177 positive) | AUC of 84%, accuracy of 82%, sensitivity of 92%, PPV of 83%, and specificity of 65% |
| Tschoellitsch et al. [52] | Leukocyte count, RDW, hemoglobin, serum calcium | RF | 1528 patients (65 positive) | Accuracy of 81%, area under the ROC curve of 0.74, sensitivity of 60%, and specificity of 82% |
| Trodjman et al. [55]; diagnosis of COVID-19 | Lymphocyte, eosinophil, basophil, and neutrophil cell count | Binary LR | 400 total patients (258 positive) | AUC of 88.9%, sensitivity of 80.3%, and PPV of 92.3% |
| Shoer et al. [54]; diagnosis of COVID-19 | Age, gender, prior medical conditions, smoking habits, fever, sore throat, cough, shortness of breath, loss of taste or smell | LR | 43,752 surveys (498 self-reported COVID-19 positive) | AUC of 0.737 |
| Joshi et al. [53]; diagnosis of COVID-19 | Neutrophil count, absolute lymphocyte count, hematocrit, male sex | LR | 2777 patients (368 PCR positive) | C-statistic of 78%, sensitivity of 86–93%, and specificity of 35–55% |
| Yang et al. [45]; diagnosis of COVID-19 | LDH, ferritin, CRP, calcuim, lymphocytes | LR, DT, RF, and (GBDT, selected) | 5893 patients (1402 positive) | AUC 83.8%, sensitivity 75.8%, and specificity reached 74% with an independent data set |
| Soltan et al. [56]; diagnosis of COVID-19 | Eosinophils, basophils, and CRP, calcium, presentation oxygen requirement, respiratory rate | LR, RF and (XGBDT, selected) | 114,957 patients (437 positive) | Emergency department and admissions models: AUCs of 88.1% and 87.1%, and accuracies of 92.3% and 92.5% respectively |
| Alakus and Turkoglu [58]; diagnosis of COVID-19 | [not mentioned] | ANN, CNN, RNN, CNNLSTM, and CNNRNN, and (LSTM, selected) | 600 patients (80 positive) | AUC of 62.50%, accuracy of 86.66%, recall of 99.42% |
| Cabitza et al. [19]; diagnosis of COVID-19 | Age, LDH, AST, CRP, calcium, fibrinogen, XDPs, WBC | RF, NB, LR, SVM, and k- KNN | 1624 patients (52% COVID-19 positive) | AUC ranged from 83% to 90% |
| Goodman-Meza et al. [59]; diagnosis of COVID-19 | Inflammatory markers, especially LDH, CRP, and the combination of CRP, LDH, and ferritin | RF, LR, SVM, multilayer perceptron, stochastic gradient descent, XGBoost, and ADABoost | 1455 records (182 positive) | AUC of 91%, sensitivity of 93%, specificity of 64% |
| Aljame et al. [60]; diagnosis of COVID-19 | Monocytes, platelets, leukocytes, urea, potassium, eosinophils, hemoglobin, lymphocytes, CRP (from highest to lowest) | RF, extra trees and LR as a first level, then XGBoost for the second level | 5644 patients (559 positive) | AUC of 99.38%, sensitivity of 98.72% and specificity of 99.99% |
| Feng et al. [61]; diagnosis COVID-19 | Age, IL-6, systolic blood pressure, monocyte %, fever classification | LR, Ridge regularization, DT, ADABoost, and Lasso regression (selected) | 132 patients (26 positive) | AUC of 84.1% F-1 score of 0.571, recall of 1.000, specificity of 0.727, and precision of 0.400 |
| Soares et al. [62]; diagnosis COVID-19 | [not mentioned]. All 16 features used: mean platelet volume, leukocytes, MCV, creatinine, red blood cells, basophils, monocytes, potassium, lymphocytes, MCHC, RDW, sodium, MCHC, eosinophils, CRP, urea | SVM, SMOTEBoost, and ensembling | 599 patients (81 positive) | Specificity of 92.16%, NPV of 95.29%, and sensitivity of 63.98% |