From: Cervical cancer survival prediction by machine learning algorithms: a systematic review
Characteristics | Categories | Number (n) | ||
---|---|---|---|---|
OS | DFS | PFS | ||
Location | Asia | 1 [19] | ||
Europe | 1 [24] | 1 [25] | ||
USA | 1 [28] | - | 1 [28] | |
Dataset sources | Hospitals | |||
SEER | 1 [17] | - | - | |
TCGA | 1 [20] | - | - | |
GEO | - | 1 [18] | - | |
Dataset privacy | Public | 1 [18] | - | |
Private | ||||
Data source | Single | |||
Multiple | 1 [21] | 1 [19] | ||
Preprocessing | Yes | 1 [19] | ||
No | 1 [21] | |||
Feature selection | Yes | |||
No | 1 [27] | - | - | |
# Models | One | - | ||
Two or more | ||||
Models type | RF | |||
LR | 1 [19] | |||
SVM | 1 [24] | - | ||
DL | - | |||
H&E L | 1 [19] | |||
Validation | Internal | |||
External | - | - | ||
Evaluation metrics | AUC | 1 [25] | ||
C-index | 1 [19] | |||
Sensitivity | 1 [27] | - | ||
Precision | - | 1 [25] | ||
Specificity | 1 [27] | 1 [22] | - | |
Accuracy | 1 [27] | 1 [25] | ||
F1-score | - | - | ||
MAE | 1 [21] | 1 [28] | ||
NPV / PPV | - | 1 [22] | - | |
Data types | Clinical | 1 [21] | ||
Image | 1 [26] | - | - | |
Molecular | - | 1 [18] | - | |
Clinical + Image | 1 [23] | 1 [25] | ||
Clinical + Molecular | 1 [20] | - | - |