Risk scoring for prediction of acute cardiac complications from imbalanced clinical data.

Fast and accurate risk stratification is essential in the emergency department (ED) as it allows clinicians to identify chest pain patients who are at high risk of cardiac complications and require intensive monitoring and early intervention. In this paper, we present a novel intelligent scoring system using heart rate variability, 12-lead electrocardiogram (ECG), and vital signs where a hybrid sampling-based ensemble learning strategy is proposed to handle data imbalance. The experiments were conducted on a dataset consisting of 564 chest pain patients recruited at the ED of a tertiary hospital.

Clinical audit of the microbiology of otorrhoea referred to a tertiary hospital in Singapore.

Introduction: Otorrhoea is a common complaint in Ear, Nose and Throat clinics. This study aimed to establish the pathogens involved in cases of otorrhoea in Singapore, their sensitivity patterns and the effectiveness of empirical management.

Methods: A retrospective chart review was conducted on 91 patients with otorrhoea who had undergone swab cultures between July 2010 and February 2011.