Search results for "NETWORKS"
showing 10 items of 3260 documents
Is neural network better than logistic regression in death prediction in patients after ST-segment elevation myocardial infarction?
2021
Background: There is a need to develop patient classification methods to adjust post-discharge care, improving survival after ST-segment elevation myocardial infarction (STEMI). Aims: The study aimed to determine whether a neural network (NN) is better than logistic regression (LR) in mortality prediction in STEMI patients. Material and methods: The study included patients from the Polish Registry of Acute Coronary Syndromes (PL-ACS). Patients with the first anterior STEMI treated with the primary percutaneous coronary intervention (pPCI) of the left anterior descending (LAD) artery between 2009 and 2015 and discharged alive were included in the study. Patients were randomly divided into th…
Predicting survival after transarterial chemoembolization for hepatocellular carcinoma using a neural network: A Pilot Study.
2019
BACKGROUND AND AIMS Deciding when to repeat and when to stop transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC) can be difficult even for experienced investigators. Our aim was to develop a survival prediction model for such patients undergoing TACE using novel machine learning algorithms and to compare it to conventional prediction scores, ART, ABCR and SNACOR. METHODS For this retrospective analysis, 282 patients who underwent TACE for HCC at our tertiary referral centre between January 2005 and December 2017 were included in the final analysis. We built an artificial neural network (ANN) including all parameters used by the aforementioned risk scores a…
General Adaption Framework
2005
Integration of heterogeneous applications and data sources into an interoperable system is one of the most relevant challenges for many knowledge-based corporations nowadays. Development of a global environment that would support knowledge transfer from human experts to automated Web services, which are able to learn, is a very profit-promising and challenging task. The domain of industrial maintenance is not an exception. This paper outlines in detail an approach for adaptation of heterogeneous Web resources into a unified environment as a first step toward interoperability of smart industrial resources, where distributed human experts and learning Web services are utilized by various devi…
Web Personalization : The State of the Art and Future Avenues for Research and Practice
2016
Provide a review of current developments in web personalization.Show evolution toward more complex contextualized approaches.Identify research gaps in web personalization and in six specific research streams.Propose web personalization to be complemented with interpolated approaches. Although web personalization has been examined by earlier literature reviews, an updated analysis of recent advances in the field is needed. The authors extend prior reviews of web personalization by discussing current areas of interest, research gaps and future directions. A literature review of the top 20 marketing and information systems journals published during the period of 2005-2015 (May) shows active re…
Towards a Framework for Agent-Enabled Semantic Web Service Composition
2004
The article presents the framework for agent-enabled dynamic Web service composition. The core of the methodology is the new understanding of a Web service as an agent capability having proper ontological description. It is demonstrated how diverse Web services may be composed and mediated by dynamic coalitions of software agents collaboratively performing tasks for service requestors. Middle Agent Layer is introduced to conduct service request to task transformation, agent-enabled cooperative task decomposition and performance. Discussed are the formal means to arrange agents’ negotiation, to represent the semantic structure of the task-activity-service hierarchy and to assess fellow-agent…
An Integrated Framework for Web Services Orchestration
2009
International audience; Currently, Web services give place to active research and this is due both to industrial and theoretical factors. On one hand, Web services are essential as the design model of applications dedicated to the electronic business. On the other hand, this model aims to become one of the major formalisms for the design of distributed and cooperative applications in an open environment (the Internet). In this article, the authors will focus on two features of Web services. The first one concerns the interaction problem: given the interaction protocol of a Web service described in BPEL, how to generate the appropriate client? Their approach is based on a formal semantics fo…
Enhanced prediction of hemoglobin concentration in a very large cohort of hemodialysis patients by means of deep recurrent neural networks.
2019
Erythropoiesis Stimulating Agents (ESAs) have become a standard anemia management tool for End Stage Renal Disease (ESRD) patients. However, dose optimization constitutes an extremely challenging task due to huge inter and intra-patient variability in the responses to ESA administration. Current data-based approaches to anemia control focus on learning accurate hemoglobin prediction models, which can be later utilized for testing competing treatment choices and choosing the optimal one. These methods, despite being proven effective in practice, present several shortcomings which this paper intends to tackle. Namely, they are limited to a small cohort of patients and, even then, they fail to…
A CAD system for nodule detection in low-dose lung CTs based on region growing and a new active contour model
2007
A computer-aided detection (CAD) system for the selection of lung nodules in computer tomography (CT) images is presented. The system is based on region growing (RG) algorithms and a new active contour model (ACM), implementing a local convex hull, able to draw the correct contour of the lung parenchyma and to include the pleural nodules. The CAD consists of three steps: (1) the lung parenchymal volume is segmented by means of a RG algorithm; the pleural nodules are included through the new ACM technique; (2) a RG algorithm is iteratively applied to the previously segmented volume in order to detect the candidate nodules; (3) a double-threshold cut and a neural network are applied to reduce…
Ambulatory Treatment and Telemonitoring of Patients with Parkinson’s Disease
2011
Body sensor networks (BSN) promise to enhance quality of life in common human habitats. The very next and natural step towards the improvement of the already valuable applications based on BSN is the incorporation of body actuator devices which adapt its actuation dynamically based on the information provided by the body sensors, thus forming Body Sensor and actuator Networks (BS&AN). This paper shows how BS&AN can be exploited to create an innovative system to support the treatment of patients affected by Parkinson’s Disease (PD). The combination of clinical and technological knowledge in BS&AN allows to significantly improve the quality of life of patients suffering from PD.
Dropout from exercise randomized controlled trials among people with depression: A meta-analysis and meta regression
2015
Abstract Objective Exercise has established efficacy in improving depressive symptoms. Dropouts from randomized controlled trials (RCT’s) pose a threat to the validity of this evidence base, with dropout rates varying across studies. We conducted a systematic review and meta-analysis to investigate the prevalence and predictors of dropout rates among adults with depression participating in exercise RCT’s. Method Three authors identified RCT’s from a recent Cochrane review and conducted updated searches of major electronic databases from 01/2013 to 08/2015. We included RCT’s of exercise interventions in people with depression (including major depressive disorder (MDD) and depressive symptoms…