Lung cancer is one of the most common malignancies and has a low 5-year survival rate. There are no cheap, simple and widely available screening methods for the early diagnostics of lung cancer. The aim of this study was to determine whether analysis...
BACKGROUND: Robot-assisted radical prostatectomy (RARP) has now become a gold standard approach in radical prostatectomy. The aim of this study was to investigate incidence and risk factors of inguinal hernia (IH) after RARP.
Acta obstetricia et gynecologica Scandinavica
Mar 6, 2017
INTRODUCTION: The objective was to assess the impact of robot-assisted radical hysterectomy (RRH) on surgical and oncologic outcome and costs compared with open radical hysterectomy (ORH) at a tertiary referral center in Sweden.
BACKGROUND: Small pancreatic neuroendocrine tumors (PNETs) are a unique subset of pancreatic neoplasms. Chromogranin A (CgA) levels, mitotic rate, and histologic differentiation are often used to characterize PNET behavior. This study evaluates the i...
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...
This was a retrospective study to investigate the predictive and prognostic ability of quantitative computed tomography phenotypic features in patients with non-small cell lung cancer (NSCLC). 661 patients with pathological confirmed as NSCLC were en...
OBJECTIVE: The Phase III, randomized, open-label IPASS study (NCT00322452) of first-line epidermal growth factor receptor tyrosine kinase inhibitor (EGFR TKI) gefitinib versus carboplatin/paclitaxel for Asian patients with advanced non-small-cell lun...
BACKGROUND: Objectives of this work are to (1) present an ontological framework for the TNM classification system, (2) exemplify this framework by an ontology for colon and rectum tumours, and (3) evaluate this ontology by assigning TNM classes to re...
PURPOSE: Extracting information from electronic medical record is a time-consuming and expensive process when done manually. Rule-based and machine learning techniques are two approaches to solving this problem. In this study, we trained a machine le...