Personalized Temporal Medical Alert System

International audienceThe continuous increasing needs in telemedicine and healthcare, accentuate the need of well-adapted medical alert systems. Such alert systems may be used by a variety of patients and medical actors, and should allow monitoring a wide range of medical variables. This paper proposes Tempas, a personalized temporal alert system. It facilitates customized alert configuration by using linguistic trends. The trend detection algorithm is based on data normalization, time series segmentation, and segment classification. It improves state of the art by treating irregular and regular time series in an appropriate way, thanks to the introduction of an observation variable valid time. Alert detection is enriched with quality and applicability measures. They allow a personalized tuning of the system to help reducing false negatives and false positives alert

Patient-Monitoring Systems

book chapterBiomedical Informatic

Report on the Information Retrieval Festival (IRFest2017)

The Information Retrieval Festival took place in April 2017 in Glasgow. The focus of the workshop was to bring together IR researchers from the various Scottish universities and beyond in order to facilitate more awareness, increased interaction and reflection on the status of the field and its future. The program included an industry session, research talks, demos and posters as well as two keynotes. The first keynote was delivered by Prof. Jaana Kekalenien, who provided a historical, critical reflection of realism in Interactive Information Retrieval Experimentation, while the second keynote was delivered by Prof. Maarten de Rijke, who argued for more Artificial Intelligence usage in IR solutions and deployments. The workshop was followed by a "Tour de Scotland" where delegates were taken from Glasgow to Aberdeen for the European Conference in Information Retrieval (ECIR 2017

Patient-Monitoring Systems

book chapterBiomedical Informatic

Patient Monitoring Systems

book chapterBiomedical Informatic

Product Innovation and Growth: The Case of Integrated Circuits

A puzzling evidence stemming from the applied research on growth and innovation is that successful innovations do not appear to have a significant effect on sales growth rates, at odds with the expectation that successful innovators will prosper at the expenses of their less able competitors. The present paper tests a research hypothesis claiming that the level of observation at which applied research is typically conducted hampers the identification of a significant association between innovation and sales growth rates. Exploiting a unique and original database comprising detailed information on product innovations by leading semiconductor companies, we find components commercialized in the nearest past to positively affect the stream of corporate revenues.Firm Growth; Product Innovation; Semiconductor industry

A theoretical framework for research on readmission risk prediction

On the one hand, predictive analytics is an important field of research in Information Systems (IS); however, research on predictive analytics in healthcare is still scarce in IS literature. One area where predictive analytics can be of great benefit is with regard to unplanned readmissions. While a number of studies on readmission prediction already exists in related research areas, there are few guidelines to date on how to conduct such analytics projects. To address this gap the paper presents the general process to develop empirical models by Shmueli and Koppius (2011) and extends this to the specific requirements of readmission risk prediction. Based on a systematic literature review, the resulting process defines important aspects of readmission prediction. It also structures relevant questions and tasks that need to be taken care of in this context. This extension of the guidelines by Shmueli and Koppius (2011) provides a best practice as well as a template that can be used in future studies on readmission risk prediction, thus allowing for more comparable results across various research fields

Artificial Gravity Reveals that Economy of Action Determines the Stability of Sensorimotor Coordination

Background: When we move along in time with a piece of music, we synchronise the downward phase of our gesture with the beat. While it is easy to demonstrate this tendency, there is considerable debate as to its neural origins. It may have a structural basis, whereby the gravitational field acts as an orientation reference that biases the formulation of motor commands. Alternatively, it may be functional, and related to the economy with which motion assisted by gravity can be generated by the motor system