Estimation of Low-Density Lipoprotein Cholesterol Concentration Using Machine Learning
Lab Medicine, cilt.53, sa.2, ss.161-171, 2022 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 53 Sayı: 2
- Basım Tarihi: 2022
- Doi Numarası: 10.1093/labmed/lmab065
- Dergi Adı: Lab Medicine
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, CINAHL, EMBASE, MEDLINE
- Sayfa Sayıları: ss.161-171
- Anahtar Kelimeler: low-density lipoproteins, cholesterol, lipids, artificial intelligence, machine learning, lipoproteins, LDL-CHOLESTEROL, CLINICAL-CHEMISTRY, EQUATION
- Ankara Üniversitesi Adresli: Evet
Özet
© American Society for Clinical Pathology, 2021. All rights reserved.Objective: Low-density lipoprotein cholesterol (LDL-C) can be estimated using the Friedewald and Martin-Hopkins formulas. We developed LDL-C prediction models using multiple machine learning methods and investigated the validity of the new models along with the former formulas. Methods: Laboratory data (n = 59,415) on measured LDL-C, high-density lipoprotein cholesterol, triglycerides (TG), and total cholesterol were partitioned into training and test data sets. Linear regression, gradient-boosted trees, and artificial neural network (ANN) models were formed based on the training data. Paired-group comparisons were performed using a t-test and the Wilcoxon signed-rank test. We considered P values <.001 with an effect size >.2 to be statistically significant. Results: For TG ≥177 mg/dL, the Friedewald formula underestimated and the Martin-Hopkins formula overestimated the LDL-C (P <.001), which was more significant for LDL-C <70 mg/dL. The linear regression, gradient-boosted trees, and ANN models outperformed the aforementioned formulas for TG ≥177 mg/dL and LDL-C <70 mg/ dL based on a comparison with a homogeneous assay (P >.001 vs. P <.001) and classification accuracy. Conclusion: Linear regression, gradient-boosted trees, and ANN models offer more accurate alternatives to the aforementioned formulas, especially for TG 177 to 399 mg/dL and LDL-C <70 mg/dL.