Early hospital mortality prediction is critical as intensivists strive to make efficient medical decisions about the severely ill patients staying in intensive care units. As a result, various methods have been developed to address this problem based on clinical records. However, some of the laboratory test results are time-consuming and need to be processed. In this paper, we propose a novel m...

We present an automatic mortality prediction scheme based on the unstructured textual content of clinical notes. Proposing a convolutional document embedding approach, our empirical investigation using the MIMIC-III intensive care database shows significant performance gains compared to previously employed methods such as latent topic distributions or generic doc2vec embeddings. These improveme...

Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person's photograph. To test this claim, we invited 12 suc...

INTRODUCTION Copeptin has been proposed as a prognostic marker in acute illness. This study investigated the ability of copeptin to predict the disease outcome and cerebrovasospasm in the patients with aneurysmal subarachnoid hemorrhage. METHODS In this retrospective study, 303 consecutive patients were included. Upon admission, plasma copeptin levels were measured by enzyme-linked immunosorb...

BACKGROUND A prospective regional study was conducted to identify factors associated with in-hospital mortality among patients undergoing isolated coronary artery bypass graft surgery (CABG). A prediction rule was developed and validated based on the data collected. METHODS AND RESULTS Data from 3,055 patients were collected from five clinical centers between July 1, 1987, and April 15, 1989....

Trauma is the leading cause of death between the ages of 1 to 44. A large number of these deaths occur within days of the arrival of the patient at the hospital. Accurate prediction of the outcomes of trauma patients and the identification of a few key predictors would be highly valuable. In this paper we focus on (1) the prediction of mortality within any given time frame after arrival, and (2...