Search results for "Artificial"
showing 10 items of 7394 documents
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…
A Multi-Variate Predictability Framework to Assess Invasive Cardiac Activity and Interactions during Atrial Fibrillation
2017
Objective: This study introduces a predictability framework based on the concept of Granger causality (GC), in order to analyze the activity and interactions between different intracardiac sites during atrial fibrillation (AF). Methods: GC-based interactions were studied using a three-electrode analysis scheme with multi-variate autoregressive models of the involved preprocessed intracardiac signals. The method was evaluated in different scenarios covering simulations of complex atrial activity as well as endocardial signals acquired from patients. Results: The results illustrate the ability of the method to determine atrial rhythm complexity and to track and map propagation during AF. Conc…
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…
Diagnostic of craniofacial asymmetry : literature review
2009
Facial asymmetry is a common feature in many syndromes, and requires surgery as the only valid treatment option. Routine diagnostic methods (frontal RX, panoramic RX and submentovertex RX) have serious limitations mainly due to the transfer from a three dimensional image to a two dimensional plane. The feasibility of such methods is poorly supported due to inherent projection errors (image magnification, cranial rotation) and identification errors (image quality, precision and reproducibility). The use of computer tomographies represents a substantial improvement in the sense of skeletal and soft tissue structures? reproduction precision. The interpretation of this new data source makes evi…
Dynamic, Behavior-Based User Profiling Using Semantic Web Technologies in a Big Data Context
2013
pp. 363-372; International audience; The success of shaping the e-society is crucially dependent on how well technology adapts to the needs of each single user. A thorough understanding of one's personality, interests, and social connections facilitate the integration of ICT solutions into one's everyday life. The MindMinings project aims to build an advanced user profile, based on the automatic processing of a user's navigation traces on the Web. Given the various needs underpinned by our goal (e.g. integration of heterogeneous sources and automatic content extraction), we have selected Semantic Web technologies for their capacity to deliver machine-processable information. Indeed, we have…
Snapshot multi-spectral-line imaging for applications in dermatology and forensics
2019
Performance of multi-spectral imaging critically depends on image acquisition time and working spectral bandwidths. Ultimate performance can be achieved if a set of monochromatic (single-wavelength) spectral images is obtained by a single snapshot - a technique provisionally called “snapshot multi-spectral-line imaging” or SMSLI. The SMSLI principle and the developed prototype devices for 3, 4 and 5 spectral line snapshot imaging are described. Two potential practical applications of SMSLI are discussed – for fast mapping of the main in-vivo skin chromophores and for detection of counterfeit banknotes and documents.
Increasing power to predict mild cognitive impairment conversion to Alzheimer's disease using hippocampal atrophy rate and statistical shape models
2010
Identifying mild cognitive impairment (MCI) subjects who will convert to clinical Alzheimer's disease (AD) is important for therapeutic decisions, patient counselling and clinical trials. Hippocampal volume and rate of atrophy predict clinical decline at the MCI stage and progression to AD. In this paper, we create p-maps from the differences in the shape of the hippocampus between 60 normal controls and 60 AD subjects using statistical shape models, and generate different regions of interest (ROI) by thresholding the p-maps at different significance levels. We demonstrate increased statistical power to classify 86 MCI converters and 128 MCI stable subjects using the hippocampal atrophy rat…
Integrated case scripts to enhance diagnostic competency
2015
Background The overwhelmingly high burden of disease and disorder especially in developing countries requires oral physicians to provide optimal dental treatment without complicating individuals’ general health. The opportunity for learners to extract the multiple aspects of a systemic condition and to relate them with the presenting complaint in order to devise an appropriate dental treatment plan is limited by time in chair- side teaching. To overcome the necessity of exposing students to real patients with varying degrees of underlying disease, those in medical and nursing education unanimously employ imaginary scenarios similar to real cases. However, such clinical scripts are seldom pr…
Neuro-radiosurgery treatments: MRI brain tumor seeded image segmentation based on a cellular automata model
2016
Gross Tumor Volume (GTV) segmentation on medical images is an open issue in neuro-radiosurgery. Magnetic Resonance Imaging (MRI) is the most promi-nent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a mini-invasive technique used to deal with inaccessible or insufficiently treated tumors. During the planning phase, the GTV is usually contoured by radiation oncologists using a manual segmentation procedure on MR images. This methodology is certainly time-consuming and op-erator-dependent. Delineation result repeatability, in terms of both intra- and inter-operator reliability, is only obtained by using computer-assisted appr…
Head–Neck Cancer Delineation
2021
Head–Neck Cancer (HNC) has a relevant impact on the oncology patient population and for this reason, the present review is dedicated to this type of neoplastic disease. In particular, a collection of methods aimed at tumor delineation is presented, because this is a fundamental task to perform efficient radiotherapy. Such a segmentation task is often performed on uni-modal data (usually Positron Emission Tomography (PET)) even though multi-modal images are preferred (PET-Computerized Tomography (CT)/PET-Magnetic Resonance (MR)). Datasets can be private or freely provided by online repositories on the web. The adopted techniques can belong to the well-known image processing/computer-vision a…