Development of a machine learning model for prediction of intraventricular hemorrhage in premature neonates.

Purpose: Intraventricular hemorrhage (IVH) is a common and severe complication in premature neonates, leading to long-term neurological impairments. Early prediction and identification of risk factors for IVH in premature neonates are crucial for improving clinical outcomes. This study aimed to predict IVH in premature neonates and determine risk factors using machine learning (ML) algorithms.

Comparison of Anterior, Posterior, and Combined Surgical Approaches on the Outcomes of Patients Suffering from Subaxial Cervical Spine Injuries.

Objective: To investigate the radiological and clinical outcomes of different surgical approaches in cervical spinal trauma in northeastern of Iran.

Methods: The present study was conducted retrospectively from January 2011 to December 2017 in Mashhad, Iran. The demographic characteristics, hospitalization duration, and patient's surgery detail data were extracted from the patients' medical records.

Soluble Fas might serve as a diagnostic tool for gastric adenocarcinoma.

Background: Fas (Apo-1/CD95) and its specific ligand (FasL) are key elements in apoptosis. They have been studied in different malignancies but there are few published studies about the soluble forms of these markers (i.e.