gene testing is a difficult, expensive, and time-consuming test which requires excessive work load. The identification of the gene mutations is significantly important in the selection of treatment and the risk of secondary cancer. We aimed to deve...
INTRODUCTION: Hematological indices including red cell distribution width and neutrophil to lymphocyte ratio are proven to be associated with outcomes of acute coronary syndrome. The usefulness of machine learning techniques in predicting mortality a...
Patients with generalized pustular psoriasis (GPP) often present with symptoms that must be differentiated from sepsis. Procalcitonin (PCT) and presepsin (P-SEP) are widely used as biomarkers for sepsis; therefore, we examined the serum PCT and P-SEP...
Using kernel machine learning (ML) and random optimization (RO) techniques, we recently developed a set of venous thromboembolism (VTE) risk predictors, which could be useful to devise a web interface for VTE risk stratification in chemotherapy-treat...
The development of breast cancer is influenced by the adipose tissue through the proteins leptin and adiponectin. However, there is little research concerning AdipoR1 and AdipoR2 receptors and the influence of leptin over them. The objective of this ...
Identification of factors that can predict the subtypes of lung adenocarcinoma preoperatively is important for selecting the appropriate surgical procedure and for predicting postoperative survival. We retrospectively evaluated 87 patients with lun...
BACKGROUND: To investigate the clinical significance of the perioperative CA19-9 change for predicting survival in intrahepatic cholangiocarcinoma (ICC) patients treated with surgical resection.
AIM: To investigate the correlation and significance between the urine soluble Fas (sFas) and vascular endothelial growth factor (VEGF) expression in patients with urothelial bladder carcinoma (UC).