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©The Author(s) 2022.
Artif Intell Gastroenterol. Jun 28, 2022; 3(3): 80-87
Published online Jun 28, 2022. doi: 10.35712/aig.v3.i3.80
Published online Jun 28, 2022. doi: 10.35712/aig.v3.i3.80
Ref. | Patients | Investigated biomarker | Model with best performance | Results |
Sowa et al[32], 2013 | 126 patients | Alanine aminotransferase; Aspartate aminotransferase; M30; M60; Hyaluronic acid | Randon forest | 79% Accuracy in fibrosis prediction; 60% sensitivity; 77% specificity |
Yip et al[33], 2017 | 922 patients | Alanine aminotransferase; High-density lipoprotein cholesterol; Triglycerides; HbA1c; White blood cells; Hypertension | Ridge score | 88% Accuracy in steatosis prediction; 92% sensitivity; 90% specificity |
Ma et al[34], 2018 | 10.508 patients; 2522 NAFLD patients | Age; Sex; Body mass index; Alanine aminotransferase; Aspartate aminotransferase; Alkaline phosphatase; Gamma-glutamyl transpeptidase; Triglycerides; Blood urea nitrogen; Bilirubin; Cholesterol; Creatinine; Fasting glucose; Uric acid | Bayesian network model | 83% Accuracy in NAFLD prediction; 68% sensitivity; 94% specificity |
Canbay et al[35], 2019 | 164 patients; 122 (validation) | Age; HbA1c; Gamma-glutamyl transpeptidase; M30; Adiponectin | Logistic regression | 70% Accuracy in separate NAFLD and NASH |
Liu et al[36], 2021 | 15.315 patients5878 with NAFLD | Body mass index; Waist circumference; Waist-to-height ratio; Alanine aminotransferase; Fasting blood glucose; Gamma-glutamyl transpeptidase; Very-low-density lipoprotein cholesterol; Low-density lipoprotein cholesterol; High-density lipoprotein cholesterol; Systolic blood pressure; Alkaline phosphatase; Diastolic blood pressure | XGBoost model | 79% Accuracy in NAFLD prediction; 61% sensitivity; 90% specificity |
Pei et al[37], 2021 | 3.419 patients; 845 with fat liver diseases | Age; Height; Hemoglobin; Aspartate aminotransferase; Glucose; Uric acid; Low-density lipoprotein; Alpha-fetoprotein; Triglycerides; High-density lipoprotein; Carcinoembryonic antigen | XGBoost model | 94% accuracy of prediction; 90% sensitivity; 95% specificity |
- Citation: Carteri RB, Grellert M, Borba DL, Marroni CA, Fernandes SA. Machine learning approaches using blood biomarkers in non-alcoholic fatty liver diseases. Artif Intell Gastroenterol 2022; 3(3): 80-87
- URL: https://www.wjgnet.com/2644-3236/full/v3/i3/80.htm
- DOI: https://dx.doi.org/10.35712/aig.v3.i3.80