Yazar "Bal, T" seçeneğine göre listele

Listeleniyor 1 - 1 / 1
  • [ X ]
    Öğe
    Assisting the Diagnosis of Cirrhosis in Chronic Hepatitis C Patients Based on Machine Learning Algorithms: A Novel Non-Invasive Approach
    (WILEY, 2025) Dirican, E; Bal, T; Önlen, Y; Sarıgül, F; User, U; Sarı, ND; Kurtaran, B; Şenateş, E; Gündüz, A; Zerdali, E; Karsen, H; Batırel, A; Karaali, R; Güner, HR; Yamazhan, T; Köse, S; Erben, N; İnce, NK; Köksal, İ; Öztoprak, N; Yoruk, G; Komur, S; Kaya, SY; Bozkurt, İ; Günal, O; Yıldız, İE; İnan, D; Barut, S; Namıduru, M; Tosun, S; Türker, K; Şener, A; Hizel, K; Baykam, N; Duygu, F; Bodur, H; Can, G; Gül, HC; Tartar, AS; Çelebi, G; Sünnetçioğlu, M; Karabay, O; Karaosmanoğlu, HK; Şirmatel, F; Tabak, OF
    Aim: This study aimed to determine the important features and cut-off values after demonstrating the detectability of cirrhosis using routine laboratory test results of chronic hepatitis C (CHC) patients in machine learning (ML) algorithms. Methods: This retrospective multicenter (37 referral centers) study included the data obtained from the Hepatitis C Turkey registry of 1164 patients with biopsy-proven CHC. Three different ML algorithms were used to classify the presence/absence of cirrhosis with the determined features. Results: The highest performance in the prediction of cirrhosis (Accuracy = 0.89, AUC = 0.87) was obtained from the Random Forest (RF) method. The five most important features that contributed to the classification were platelet, alpha lpha-feto protein (AFP), age, gamma-glutamyl transferase (GGT), and prothrombin time (PT). The cut-off values of these features were obtained as platelet < 182.000/mm3, AFP > 5.49 ng/mL, age > 52 years, GGT > 39.9 U/L, and PT > 12.35 s. Using cut-off values, the risk coefficients were AOR = 4.82 for platelet, AOR = 3.49 for AFP, AOR = 4.32 for age, AOR = 3.04 for GGT, and AOR = 2.20 for PT. Conclusion: These findings indicated that the RF-based ML algorithm could classify cirrhosis with high accuracy. Thus, crucial features and cut-off values for physicians in the detection of cirrhosis were determined. In addition, although AFP is not included in non-invasive indexes, it had a remarkable contribution in predicting cirrhosis. Trial Registration: Clinicaltrials.gov identifier: NCT03145844