Table 1.
A summary of recent machine learning-based studies on thyroid disease diagnosis.
| Year and reference | Data collection | Number of instances | Output classes | Balancing Technique |
Best Performing classifier |
|---|---|---|---|---|---|
| 2020 [7] | UCI | 7200 | 3 | (−) | RF |
| 2018 [8] | UCI | 3163 | 2 | (−) | LDA-KNN-ANFIS |
| 2022 [10] | UCI | 3163 | 2 | SMOTE | RF |
| 2021 [11] | Naples's hospital | 2784 | 3 | SMOTE | ET |
| 2021 [14] | Hospitals and Labs | 1250 | 3 | (−) | RF |
| 2021 [15] | UCI | 2800 | 2 | BL_SMOTE | Voting (RF, DT) |
| 2020 [16] | UCI | 215 | 3 | (−) | KNN |
| 2022 [17] | UCI | 7200 | 3 | SMOTE | ANN |
| 2021 [18] | Saudi Arabian | 218 | 2 | (−) | RF |
| 2020 [19] | UCI | 7547 | 2 | (−) | CCTML |
| 2019 [20] | Pathologies | 27000 | 3 | (−) | Stacking (DT, NN) |
| 2023 [24] | UCI | 3772 | 2 | (−) | RF |
| 2023 [25] | Kaggle | 3371 | 2 | (−) | SVM |
| 2023 [26] | UCI | 2800 | 2 | SMOTE | RF |
| 2023 [27] | Kaggle | 3773 | 2 | SMOTE | 3SHC |