Table 2.
Summary of reviewed articles in terms of outcome, evaluation metrics, and comparing methods (N=22).
| Authors | Outcomea | Evaluation metricsb | Compared againstc | |
| Jurisica et al [16] | Suggesting hormonal therapy (day of human chorionic gonadotrophin administration and the number of ampoules of human menopausal gonadotrophin) after in vitro fertilization and predicting pregnancy outcome (pregnancy, abortion, ectopic pregnancy, and ovarian hyperstimulation syndrome) | Accuracy | NR | |
| Bobrowski [17] | Four types of liver disease (cirrhosis hepatis biliaris primaria, cirrhosis hepatis decompensata, hepatitis chronica activa, and hepatitis chronica steatosis) | Accuracy | Classic k-NN (k=10) | |
| Park et al [19] | (1) Six types of dermatology diseases (psoriasis, seborrheic dermatitis, lichen planus, pityriasis rosea, chronic dermatitis, pityriasis rubra pilaris); (2) diagnosis of heart disease (angiographic disease status); (3) diagnosis of a breast tumor as malignant or benign; (4) diagnosis of diabetes; (5) diagnosis of liver disorder | Accuracy; sensitivity; specificity | LR; C5.0; CART; neural network; conventional CBR (k=5) with five neighbors | |
| Saeed et al [21] | Hemodynamic stability or instability of an episode | Sensitivity; positive predictive value | NR | |
| Chattopadhyay et al [23] | Suicidal risk levels (level 1: suicidal plans or thoughts; level 2: single suicidal attempt; level 3: multiple suicidal attempts) | NR | NR | |
| Sun et al [24] | Occurrence of acute hypotensive episode within the forecast window of an hour | Accuracy | Human expert’s idea based on the Euclidean [44]; k-NN over low-dimensional space after applying PCA | |
| Sun et al [25] | Occurrence of acute hypotensive episode within the forecast window of an hour | Accuracy | Human expert’s idea based on the Euclidean [44]; k-NN over low-dimensional space after applying PCA | |
| David et al [26] | Seven disease diagnoses (microcytic anemia, normocytic anemia, mild SIRS, thrombocytopenia, leukocytopenia, moderate/severe SIRS, normal) | Accuracy | Human expert’s idea | |
| Houeland [27] | Pain levels | Error rate (1-accuracy). | Random retrieval; k-NN (k=1) with the Euclidian distance; random forest | |
| Wang et al [28] | (1) Diagnosis of a breast tumor as malignant or benign; (2) diagnosis of diabetes; (3) diagnosis of dementia without complications (HCC352) or diabetes with no or unspecified complications (HCC019) | Accuracy; sensitivity; precision; F-measure | PCA; LDA [45]; LSDA [45]; LSML [24] | |
| Wang et al [29] | Diagnosis of CHF 6 months later | Accuracy; sensitivity; precision; F-measure | LLE; LE; PCA; Euclidean distance. | |
| Campillo-Gimenez et al [30] | Registration on the renal transplant waiting list: yes/no | ROC curve | k-NN; LR; k-NN with weighted predictors; k-NN with weighted patients | |
| Gottlieb et al [32] | Patient discharge diagnosis ICD codes | ROC curve; F-measure | NR | |
| Lowsky et al [33] | Graft survival probability | IPEC | Cox model; RSF [46] | |
| Hielscher et al [34] | Three levels of liver fat concentration measured by magnetic resonance tomography: (1) fat concentration <10%; (2) fat concentration of 10%-25%; (3) fat concentration ≥25% | Accuracy; sensitivity; specificity | Multiple variants of the k-NN: majority voting; weighted voting; with/without predictor selection |
|
| Zhang et al [36] | Four effective drugs for hypercholesterolemia treatment: atorvastatin, lovastatin, pravastatin, and simvastatin | ROC curve | Patient similarity; patient similarity with drug structure similarity; patient similarity with drug target similarity |
|
| Henriques et al [37] | Early detection of heart failure: decompensation or normal condition | Sensitivity; specificity; F-measure; G-measure | Coefficients’ distance; linear correlation of signals; Euclidean distance | |
| Lee et al [39] | 30-day in-hospital mortality | Area under ROC curve; area under precision-recall curve | Population-based and personalized versions of: majority vote; LR; DT | |
| Ng et al [40] | The risk of diabetes disease onset | ROC curve | Global LR; k-NN; patient similarity-based LR with Euclidean distance | |
| Panahiazar et al [41] | Medication plans for heart-failure patients (angiotensin-converting enzyme, angiotensin receptor blockers, β-adrenoceptor antagonists, statins, and calcium channel blocker) | Sensitivity; specificity; F-measure; accuracy | K-means; hierarchical clustering |
|
| Wang [42] | (1) Diagnosis of a breast tumor as malignant or benign; (2) diagnosis of diabetes; (3) occurrence of CHF within 6 months | Precision; F-measure; sensitivity; accuracy | kd-tree; PCA- kd-tree; ball-tree; spectral-tree. |
|
| Wang et al [43] | Occurrence of CHF within 6 months | Precision; F-measure; sensitivity; accuracy | PCA; Laplacian regularized metric learning [47]; LLE [48]; LSR; LSML [24] |
a CHF: congestive heart failure; ICD: International Classification of Diseases.
b IPEC: integrated prediction error curve ; NR: not reported; ROC: receiver operating characteristic: SIRS: systemic inflammatory response syndrome.
c CART: classification and regression tree; CBR: case-based reasoning; DT: decision tree; k-NN: k- nearest neighbor; kd-tree: k dimensional tree; LDA: linear discriminant analysis; LE: Laplacian embedding; LLE: locally linear embedding; LR: logistic regression; LSDA: locality sensitive discriminant analysis; LSML: locally supervised metric learning; LSR: local spline regression; NR: not reported; PCA: principal component analysis; RSF: random survival forest.