Fusion Symbolique et Données Polysomnographiques

In recent decades, medical examinations required to diagnose and guide to treatmentbecame more and more complex. It is even a current practice to use several examinationsin different medical specialties to study a disease through multiple approaches so as todescribe it more deeply.The interpretation is difficult because the data is both heterogeneous and also veryspecific, with skilled domain of knowledge required to analyse it.In this context, symbolic fusion appears to be a possible solution. Indeed, it wasproved to be very effective in treating problems with low or high levels of abstraction ofinformation to develop a high level knowledge.This thesis demonstrates the effectiveness of symbolic fusion applied to the treatmentof polysomnographic data for the development of an assisted diagnosis tool of Sleep ApneaSyndrome. Proper diagnosis of this sleep disorder requires a polysomnography. This medi-cal examination consists of simultaneously recording of various physiological parametersduring a night. Visual interpretation is tedious and time consuming and there commonlyis some disagreement between scorers. The use of a reliable support-to-diagnosis toolincreases the consensus. This thesis develops stages of the development of such a tool.Au cours des dernières décennies, la médecine a nécessité des examens de plus enplus complexes pour effectuer un diagnostic et orienter vers un traitement. Il est mêmecourant de pratiquer plusieurs examens dans des spécialités médicales différentes afind’étudier une pathologie par des approches multiples et ainsi mieux la connaître.Cela pose des difficultés d’interprétation car les données sont parfois hétérogènes maissurtout souvent très pointues et leur traitement requiert une expertise du domaine.Dans ce contexte, la fusion symbolique constitue une solution possible. En effet, ellea prouvé son efficacité à traiter des problèmes sur des niveaux d’abstraction aussi bienfaibles qu’élevés et à élaborer une connaissance de haut niveau.Cette thèse démontre l’efficacité de la fusion symbolique appliquée au traitement desdonnées polysomnographiques pour l’élaboration d’un outil de support au diagnostic duSyndrome d’Apnées du Sommeil. Pour être diagnostiqué, ce trouble du sommeil nécessiteune polysomnographie. Cet examen médical consiste en l’enregistrement simultané dedivers paramètres physiologiques durant toute une nuit. Son interprétation nécessitel’annotation des courbes enregistrées par une analyse visuelle effectuée par un médecinspécialiste du sommeil, ce qui est une tâche chronophage et fastidieuse dont les résultatspeuvent présenter quelques divergences d’un expert à l’autre. Le recours à un outil desupport au diagnostic fiable permet d’augmenter le consensus. Cette thèse développe lesétapes d’élaboration d’un tel outil

Automatic Sleep Stages Classification Combining Semantic Representation and Dynamic Expert System

International audienceInterest in sleep has been growing in the last decades, considering its benefits for well-being, but also to diagnose sleep troubles. The gold standard to monitor sleep consists of recording the course of many physiological parameters during a whole night. The human interpretation of resulting curves is time consuming. We propose an automatic knowledge-based decision system to support sleep staging. This system handles temporal data, such as events, to combine and aggregate atomic data, so as to obtain high-abstraction-levels contextual decisions. The proposed system relies on a semantic reprentation of observations, and on contextual knowledge base obtained by formalizing clinical practice guidelines. Evaluated on a dataset composed of 131 full night polysomnographies, results are encouraging, but point out that further knowledge need to be integrated

Automatic Cyclic Alternating Pattern (CAP) analysis: Local and multi-trace approaches

: The Cyclic Alternating Pattern (CAP) is composed of cycles of two different electroencephalographic features: an activation A-phase followed by a B-phase representing the background activity. CAP is considered a physiological marker of sleep instability. Despite its informative nature, the clinical applications remain limited as CAP analysis is a time-consuming activity. In order to overcome this limit, several automatic detection methods were recently developed. In this paper, two new dimensions were investigated in the attempt to optimize novel, efficient and automatic detection algorithms: 1) many electroencephalographic leads were compared to identify the best local performance, and 2) the global contribution of the concurrent detection across several derivations to CAP identification. The developed algorithms were tested on 41 polysomnographic recordings from normal (n = 8) and pathological (n = 33) subjects. In comparison with the visual CAP analysis as the gold standard, the performance of each algorithm was evaluated. Locally, the detection on the F4-C4 derivation showed the best performance in comparison with all other leads, providing practical suggestions of electrode montage when a lean and minimally invasive approach is preferable. A further improvement in the detection was achieved by a multi-trace method, the Global Analysis-Common Events, to be applied when several recording derivations are available. Moreover, CAP time and CAP rate obtained with these algorithms positively correlated with the ones identified by the scorer. These preliminary findings support efficient automated ways for the evaluation of the sleep instability, generalizable to both normal and pathological subjects affected by different sleep disorders

Optimization-based features extraction for K-complex detection

The K-complex is a transient electroencephalogram (EEG, brain activity) waveform that contributes to sleep stage scoring. An automated detection of K-complexes is an important component of sleep stage monitoring. This automation is difficult due to the stochastic nature of brain signals, presence of noise, complexity, and extreme size of data. We develop an optimization model, based on solving a sequence of linear least squares problems, to extract key features of EEG signals. The proposed approach significantly reduces the dimension of the problem and the computational time while the classification accuracy is enhanced in most cases. Numerical results show that this procedure is efficient in detecting K-complexes. References R. Agarwal and J. Gotman. Digital tools in polysomnography. J. Clin. Neurophysiol., 19(2):136–143, 2002. http://journals.lww.com/clinicalneurophys/Abstract/2002/03000/Digital_Tools_in_Polysomnography.4.aspx. J. L. Barlow. Numerical aspects of solving linear least squares problems. Technical report, Computer Science Department, The Pennsylvania State University, University Park, PA, USA, January 1999. www.cse.psu.edu/ barlow/book.ps. A. Bjorck. Numerical Methods for Least Squares Problems. Handbook of Numerical Analysis. SIAM, 1996. doi:10.1137/1.9781611971484. S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, New York, NY, USA, 2010. http://www.cambridge.org/au/academic/subjects/statistics-probability/optimization-or-and-risk/convex-optimization?format=HB. G. Bremer, J. R. Smith, and I. Karacan. Automatic detection of the K-complex in sleep electroencephalograms. IEEE T. Bio-Med. Eng., 17(4):314–323, 1970. doi:10.1109/TBME.1970.4502759. P. R. Carney, R. B. Berry, and J. D. Geyer. Clinical Sleep Disorders. LWW medical book collection. Lippincott Williams and Wilkins, 2005. http://www.lww.com/Product/9780781786928. G. H. Golub and C. F. Van Loan. Matrix Computations. Johns Hopkins Studies in the Mathematical Sciences. Johns Hopkins University Press, Baltimore, MD, USA, 1996. http://portal.acm.org/citation.cfm?id=248979. C. Iber, S. Ancoli-Israel, A. L. Chesson, and S. F. Quani. AASM manual for the scoring of sleep and associated events. Rules, technology and technical specifications. Technical report, AASM, Westchester, IL, 2007. http://www.aasmnet.org/scoringmanual/v2.0.2/html/index.html?IXDevelopmentProcess.html. B. H. Jansen. Artificial neural nets for K-complex detection. IEEE Eng. Med. Biol., 9(3):50–52, 1990. doi:10.1109/51.59213. A. Kales, A. Rechtschaffen, Los Angeles University of California, and NINDB Neurological Information Network (U.S.). A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects. U. S. National Institute of Neurological Diseases and Blindness, Neurological Information Network Bethesda, Md, 1968. http://nla.gov.au/nla.cat-vn823711 . J. E. Mitchell. Branch-and-cut algorithms for combinatorial optimization problems. In P. M. Pardalos and M. G. C. Resende, editors, Handbook of Applied Optimization, pages 65–77. Oxford University Press, 2002. http://global.oup.com/academic/product/handbook-of-applied-optimization-9780195125948?cc=au&lang=en&. D. Moloney, N. Sukhorukova, P. Vamplew, J. Ugon, G. Li, G. Beliakov, C. Philippe, H. Amiel, and A. Ugon. Detecting K-complexes for sleep stage identification using nonsmooth optimization. ANZIAM J., 52:319–332, 2011. doi:10.1017/S1446181112000016. O. Sheriff, B. Pagnrek, S. Mamouhd, and R. Broughton. Automatic detection of K-complex in sleep EEG. Int. Electrical Electronic Conf. Exp., 81, 1977. Z. Tang and N. Ishii. Detection of the K-complex using a new method of recognizing waveform based on the discrete wavelet transform. IEICE T. Inf. Syst., E78–D(1):77–85, 1995. http://search.ieice.org/bin/summary.php?id=e78-d_1_77. L. N. Trefethen and D. Bau. Numerical Linear Algebra. SIAM, 1997. http://bookstore.siam.org/ot50/. Weka web site. www.cs.waikato.ac.nz/ml/weka/

Data Fusion to Convert Drug Consumption Quantities into Defined Daily Doses

International audienceAnalysis of consumptions has proved a misuse of antibiotics, despite the existence of national requirements. To be able to compute drugs consumption quantities of highly heterogeneous drugs expressed in various doses units, the World Health Organization has defined a defined daily dose. A methodology has been also defined from previous work to compute manually the drugs consumptions in daily defined dose. We automated this methodology by using data fusion on data retrieved from different sources including a French public database and the World Health Organization website. Evaluation proved the efficiency of the approach, except for inconsistency cases. We identified these cases and proposed a solution to avoid them

Automatic Extraction of Drug Adverse Effects from Product Characteristics (SPCs): A Text Versus Table Comparison

International audienceBackground: Potential adverse effects (AEs) of drugs are described in their summary of product characteristics (SPCs), a textual document. Automatic extraction of AEs from SPCs is useful for detecting AEs and for building drug databases. However, this task is difficult because each AE is associated with a frequency that must be extracted and the presentation of AEs in SPCs is heterogeneous, consisting of plain text and tables in many different formats. Methods: We propose a taxonomy for the presentation of AEs in SPCs. We set up natural language processing (NLP) and table parsing methods for extracting AEs from texts and tables of any format, and evaluate them on 10 SPCs. Results: Automatic extraction performed better on tables than on texts. Conclusion: Tables should be recommended for the presentation of the AEs section of the SPCs

Comparaison et visualisation des contre-indications des médicaments

International audienceLes nouveaux médicaments représentent des opportunités de soin mais aussi des risques potentiels. Les médecins ont besoin d'une information indépendante et fiable leur permettant de comparer les nouveaux médicaments avec les anciens. La comparaison des propriétés entre médicament est cependant rendue difficile par l'expression de ces propriétés à des niveaux de granularité variables, par exemple “ maladie hémorragique ” contre “ maladie hémorragique constitutionnelle ”.Dans ce papier, nous proposons une approche à base d'ontologie formelle permettant la comparaison des contre-indications des médicaments et la génération automatique de tableaux comparatifs dynamiques

A Web Interface for Antibiotic Prescription Recommendations in Primary Care: User-Centered Design Approach

International audienceBackground: Antibiotic misuse is a serious public health problem worldwide. National health authorities release clinical practice guidelines (CPGs) to guide general practitioners (GPs) in their choice of antibiotics. However, despite the large-scale dissemination of CPGs, GPs continue to prescribe antibiotics that are not recommended as first-line treatments. This nonadherence to recommendations may be due to GPs misunderstanding the CPGs. A web interface displaying antibiotic prescription recommendations and their justifications could help to improve the comprehensibility and readability of CPGs, thereby increasing the adoption of recommendations regarding antibiotic treatment.Objective: This study aims to design and evaluate a web interface for antibiotic prescription displaying both the recommended antibiotics and their justifications in the form of antibiotic properties.Methods: A web interface was designed according to the same principles as e-commerce interfaces and was assessed by 117 GPs. These GPs were asked to answer 17 questions relating to the usefulness, user-friendliness, and comprehensibility and readability of the interface, and their satisfaction with it. Responses were recorded on a 4-point Likert scale (ranging from "absolutely disagree" to "absolutely agree"). At the end of the evaluation, the GPs were allowed to provide optional, additional free comments.Results: The antibiotic prescription web interface consists of three main sections: a clinical summary section, a filter section, and a recommended antibiotics section. The majority of GPs appreciated the clinical summary (90/117, 76.9%) and filter (98/117, 83.8%) sections, whereas 48.7% (57/117) of them reported difficulty reading some of the icons in the recommended antibiotics section. Overall, 82.9% (97/117) of GPs found the display of drug properties useful, and 65.8% (77/117) reported that the web interface improved their understanding of CPG recommendations.Conclusions: The web interface displaying antibiotic recommendations and their properties can help doctors understand the rationale underlying CPG recommendations regarding antibiotic treatment, but further improvements are required before its implementation into a clinical decision support system

OPTISAS a new method to analyse patients with Sleep Apnea Syndrome

International audienceOPTISAS is a visualization method that allows describing very precisely a patient with Sleep Apnea Syndrome. Using the events scored by the physician, our method gives a set of graphs that are a detailed representation of the condition, sleep stage and position, in which the events occur. This helps for the diagnosis. This is possible thanks to the application of Generalized Caseview method. The method proceeds in two steps, defining the reference frame and using this reference frame to visualize data. The reference frame is built by using a supin/unsupine binary criterion, a six type event criterion and a sleep stage ordinal criterion. The main result is the visualization of the indexes (average number of events by hour) associated with the events. This allows a more accurate diagnosis showing the precise influence of the position and of the sleep stage on the events