Waikato Environment for Knowledge Analysis (WEKA) as a Data Analysis Method Identifying Potential Hematological Parameters for Early Diagnosis of Cervical Cancer.

Background/aim: The present study explored the use of Waikato Environment for Knowledge Analysis (WEKA) to analyze hematological parameters for distinguishing potential development and progression of cervical cancer. Specifically, we aimed to identify significant biomarkers capable of differentiating atypical squamous cells of undetermined significance (ASC-US) and low-grade squamous intraepithelial lesions (LSIL) from cervical cancer-negative and advanced conditions such as cervical adenocarcinoma.

Materials And Methods: Hematological and biochemical data were collected from patients and analyzed using data-mining algorithms available in WEKA.