pISSN 2234-3806eISSN 2234-3814
Categorical summary of key points from the literature review of studies applying ML in laboratory medicine from February 2014 to April 2024
| Laboratory medicine field | Research objective | Specimen type | Data type | ML model | Evaluation metric and performance |
|---|---|---|---|---|---|
|
Clinical chemistry Clinical microbiology Diagnostic hematology Diagnostic immunology Molecular diagnostics Transfusion medicine |
Autoverification Classification CDS for laboratories Counting/enumeration Disease screening Error detection Estimation/prediction Recognition Tools based on AI Others Data generation/process simulation Machine learning Optimization Preprocessing assistant |
Blood Blood image WBC image Blood cell image RBC image CGM data CBC data Bone marrow Plasma Urine Urine sample Urine micrograph image Urine culture image Others Bacteria Antibiogram Sperm Stool |
Image Sequence Tabular Numeric Category Text |
CNN DNN DT MLP LR RF RNN SVM XGB Others CatBoost CNN+LSTM DBN Ensemble HCA KNN LLM PLS-DA UMAP |
AC AUROC SE SP PPV NPV F1 score FNR MSE MAE R2 RMSE |
Abbreviations: AC, accuracy; AI: artificial intelligence; AUROC, area under the ROC curve; CBC, complete blood count; CDS: clinical decision support; CGM, continuous glucose monitoring; CNN, convolutional neural network; DBN, deep belief network; DNN, deep neural network; DT, decision tree; FNR, false-negative rate; HCA, hierarchical cluster analysis; KNN, k-nearest neighbor; LLM, large language model; LR, logistic regression; LSTM, long short-term memory; MAE, mean absolute error; ML: machine learning; MLP, multilayer perceptron; MSE, mean squared error; NPV, negative predictive value; PLS-DA, partial least squares-discriminant analysis; PPV, positive predictive value; R2: coefficient of determination; RBC, red blood cell; RF, random forest; RMSE, root mean squared error; RNN, recurrent neural network; SE, sensitivity; SP, specificity; SVM, support vector machine; UMAP, uniform manifold approximation and projection; WBC, white blood cell; XGB, extreme gradient boosting.
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