AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
Targeted cancer drugs are often associated with unexpectedly high cardiovascular (CV) adverse events. Systematic approaches to studying CV events associated with targeted anticancer drugs have high potential for elucidating the complex pathways under...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
Over the last few decades, machine learning and data mining have been increasingly used for clinical prediction in ICUs. However, there is still a huge gap in making full use of the time-series data generated from ICUs. Aiming at filling this gap, we...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
Structured reporting in medicine has been argued to support and enhance machine-assisted processing and communication of pertinent information. Retrospective studies showed that structured echocardiography reports, constructed through point-and-click...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
The secondary use of electronic health records opens up new perspectives. They provide researchers with structured data and unstructured data, including free text reports. Many applications been developed to leverage knowledge from free-text reports,...
OBJECTIVE: The Internet has become a platform to express individual moods/feelings of daily life, where authors share their thoughts in web blogs, micro-blogs, forums, bulletin board systems or other media. In this work, we investigate text-mining te...
Clinical outcome prediction, as strong implications for health service delivery of clinical treatment processes (CTPs), is important for both patients and healthcare providers. Prior studies typically use a priori knowledge, such as demographics or p...
We present in this paper a novel approach based on multi-agent technology for Web information foraging. We proposed for this purpose an architecture in which we distinguish two important phases. The first one is a learning process for localizing the ...
We present a machine learning-based methodology capable of providing real-time ("nowcast") and forecast estimates of influenza activity in the US by leveraging data from multiple data sources including: Google searches, Twitter microblogs, nearly rea...