Praveen Kumar Maharana 2 1 (January - March) Hepatocellular carcinoma HCC is one of the most prevalent forms of primary liver cancer and requires timely identification to improve treatment outcomes This study proposes a machine learningbased approach for detecting HCC using Logistic Regression The proposed method analyses relevant clinical and diagnostic attributes to distinguish between patients with and without liver cancer Data preprocessing techniques are applied to improve data quality handle missing values and transform input variables into a suitable format for model training Logistic Regression is then employed to learn the relationship between the selected features and the occurrence of HCC The trained model produces a probabilitybased prediction that can assist in identifying highrisk cases Model performance can be assessed using accuracy precision recall F1score and the area under the receiver operating characteristic curve The proposed approach provides a simple interpretable and computationally efficient framework that may support early liver cancer screening and clinical decisionmaking Copyright (c) International Journal of Computational Science and Engineering Research . All rights reserved 2026