Search results

During the past decade, scholars have produced a vast amount of research using linked historical individual-level data, shaping and changing our understanding of the past. This linked data revolution has been powered by methodological and computational advances, partly focused on supervised machine-learning methods that rely on training data. The importance of obtaining high-quality training data

With the palliative care workforce shortage and changes in advance care planning reimbursement, many institutions are requesting that palliative care specialists provide serious illness communication training across their institution's workforce. Based on our experience training clinicians to use the Partners Serious Illness Conversation Guide, a structured guide to teach basic palliative care com

INTRODUCTION: The aim of this study was to compare different methods to predict acute coronary syndrome (ACS) using only data from a single electrocardiogram (ECG) in the emergency department (ED). METHOD: We compared the ACS prediction abilities of classical ECG criteria, human expert ECG interpretation, a logistic regression model and an artificial neural network ensemble (ANN). The ED ECG and d

Emergency abdominal surgery outcomes represent an internationally important marker of healthcare quality and capacity. In this study, a novel approach to investigating global surgical outcomes is proposed, involving collaborative methodology using 'snapshot' clinical data collection over a 2-week period. The primary aim is to identify internationally relevant, modifiable surgical practices (in ter

This report has been compiled within the framework of the programme on Regional Air Pollution in Developing Countries (RAPIDC), Phase III conducted during the period 2005-2008. RAPIDC is funded by the Department of Infrastructure and Economic Cooperation (INEC) of the Swedish International Development Cooperation Agency (SIDA). It is coordinated by the Stockholm Environment Institute (SEI) and car

According to Jon Elster, mechanisms are frequently occurring and easily recognizable causal patterns that are triggered under generally unknown conditions or with indeterminate consequences. In the absence of laws, moreover, mechanisms provide explanations. In this paper I argue that Elster’s view has difficulties with progressing knowledge. Normally, filling in the causal picture without revising

According to Jon Elster, mechanisms are frequently occurring and easily recognizable causal patterns that are triggered under generally unknown conditions or with indeterminate consequences. In the absence of laws, moreover, mechanisms provide explanations. In this paper I argue that Elster’s view has difficulties with progressing knowledge. Normally, filling in the causal picture without revising