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Intensive spa and exercise therapy program for returning to work for low back pain patients: a randomized controlled trial
No full textInternational audienceWe aimed to determine whether a 5-day intensive inpatient spa and exercise therapy and educational program is more effective than usual care in improving the rate of returning to work at 1 year for patients with subacute and chronic low back pain (LBP) on sick leave for 4 to 24 weeks. We conducted a 12-month randomized controlled trial. LBP patients were assigned to 5-day spa (2 hr/day), exercise (30 min/day) and education (45 min/day) or to usual care. The primary outcome was the percentage of patients returning to work at 1 year after randomization. Secondary outcomes were pain, disability and health-related quality of life at 1 year and number of sick leave days from 6 to 12 months. The projected recruitment was not achieved. Only 88/700 (12.6%) patients planned were enrolled: 45 in the spa therapy group and 43 in the usual care group. At 1 year, returning to work was 56.3% versus 41.9% (OR 1.69 [95% CI 0.60-4.73], p = 0.32) respectively. There was no significant difference for any of the secondary outcomes. However, our study lacked power
Adapting the Number of Particles in Sequential Monte Carlo Methods through an Online Scheme for Convergence Assessment
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Hölder-type inequalities and their applications to concentration and correlation bounds
No full textInternational audienceLet Y v , v ∈ V , be real-valued random variables having a dependency graph G = (V, E). We show that E ⎡ ⎣ ∏ v∈V Y v ⎤ ⎦ ≤ ∏ v∈V { E [ Y χ b b v ]} b χ b , where χ b is the b-fold chromatic number of G. This inequality may be seen as a dependency-graph analogue of a generalised Hölder inequality, due to Helmut Finner. Additionally, we provide applications of the aforementioned Hölder-type inequalities to concentration and correlation bounds for sums of weakly dependent random variables whose dependencies can be described in terms of graphs or hypergraphs
Extraction and optimization of classification rules for temporal sequences: Application to hospital data
No full textInternational audienceThis study focuses on the problem of supervised classification on heterogeneous temporal data featuring a mixture of attribute types (numeric, binary, symbolic, temporal). We present a model for classification rules designed to use both non-temporal attributes and sequences of temporal events as predicates. We also propose an efficient local search-based metaheuristic algorithm to mine such rules in large scale, real-life data sets extracted from a hospital’s information system. The proposed algorithm, MOSC (Multi-Objective Sequence Classifier), is compared to standard classifiers and previous works on these real data sets and exhibits noticeably better classification performance. While designed with medical applications in mind, the proposed approach is generic and can be used for problems from other application domains
Emotion Recognition by Body Movement Representation on the Manifold of Symmetric Positive Definite Matrices
No full textInternational audienceEmotion recognition is attracting great interest for its potential application in a multitude of real-life situations. Much of the Computer Vision research in this field has focused on relating emotions to facial expressions, with investigations rarely including more than upper body. In this work, we propose a new scenario, for which emotional states are related to 3D dynamics of the whole body motion. To address the complexity of human body movement, we used covariance descrip-tors of the sequence of the 3D skeleton joints, and represented them in the non-linear Riemannian manifold of Symmetric Positive Definite matrices. In doing so, we exploited geodesic distances and geometric means on the manifold to perform emotion classification. Using sequences of spontaneous walking under the five primary emotional states, we report a method that succeeded in classifying the different emotions, with comparable performance to those observed in a human-based force-choice classification task
From sensorimotor coordinations to the sign without representation : the emergence of the signifier at the crossroads of points of view (Chronosignifying)
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Outcome of EGFR-mutated NSCLC patients with MET-driven resistance to EGFR tyrosine kinase inhibitors
No full textInternational audienceSeveral mechanisms of acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) in EGFR-mutated NSCLC have been described including the T790M mutation and METPatients with metastatic EGFR-mutated NSCLC displaying high MET overexpression or METForty two patients were included. The median overall survival (OS), and the median post EGFR TKI progression overall survival (PPOS) were 36.2 months [95%CI 27.3-66.5] and 18.5 months [95%CI 10.6-27.4] respectively. Nineteen out of 36 tumors tested for MET FISH had METMET-driven resistance to EGFR TKI defines a specific pattern of resistance characterized by low objective response rate to MET inhibitors given alone and overlapping with T790M mutations. Further studies are warranted to define adequate therapeutic strategies for MET-driven resistance to EGFR TKI
Picasso devant la nature : [exposition, Sceaux, Musée du domaine départemental de Sceaux, 15 septembre-31 décembre 2017]
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Automatic biomechanical graph matching CT-CBCT fusion
No full textInternational audienceImage-guided hepatic surgery is progressively becoming a standard for certain interventions. However, limited dose radiation requirements result in lower quality images, making it difficult to localize tumors and other structures of interest. In this paper we propose an automatic registration method exploiting the matching of the vascular trees, visible in both pre and intra-operative images. The graphs are automatically matched using an algorithm combining a Gaussian Process Regression and biomechanical model. This process is automatic, does not require any initialization and handles large intra-operative deformations