Automatic Mallampati Classification Using Active Appearance Models

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.

Genetic diversity and differentiation processes in the ploidy series of Olea europaea L.: a multiscale approach from subspecies to insular populations.

Geographical isolation and polyploidization are central concepts in plant evolution. The hierarchical organization of archipelagos in this study provides a framework for testing the evolutionary consequences for polyploid taxa and populations occurring in isolation. Using amplified fragment length polymorphism and simple sequence repeat markers, we determined the genetic diversity and differentiation patterns at three levels of geographical isolation in Olea europaea: mainland-archipelagos, islands within an archipelago, and populations within an island. At the subspecies scale, the hexaploid ssp. maroccana (southwest Morocco) exhibited higher genetic diversity than the insular counterparts. In contrast, the tetraploid ssp. cerasiformis (Madeira) displayed values similar to those obtained for the diploid ssp. guanchica (Canary Islands). Geographical isolation was associated with a high genetic differentiation at this scale. In the Canarian archipelago, the stepping-stone model of differentiation suggested in a previous study was partially supported. Within the western lineage, an east-to-west differentiation pattern was confirmed. Conversely, the easternmost populations were more related to the mainland ssp. europaea than to the western guanchica lineage. Genetic diversity across the Canarian archipelago was significantly correlated with the date of the last volcanic activity in the area/island where each population occurs. At the island scale, this pattern was not confirmed in older islands (Tenerife and Madeira), where populations were genetically homogeneous. In contrast, founder effects resulted in low genetic diversity and marked genetic differentiation among populations of the youngest island, La Palma.

The Corrosion of Career? - Occupational Trajectories of Business Economists and Engineers in Switzerland

Achievement careers are regarded as a distinctive element of the post-war period in occidental societies. Such a career was at once a modal trajectory of the modern parts of middleclass men and a social emblem for progress and success. However, if the achievement career came to be a biographical pattern with great normative power, its precise sequential course remained vague. Theories of the 1960s and 1970s described it as an orderly advancement within large firms. By the 1990s, scholars postulated an erosion of the organizational structures that once contributed to the institutionalization of careers, accompanied by a weakening of the normative weight of the achievement career by management discourse. We question the thesis of the corrosion of achievement career by analysing the trajectories of 442 engineers and business economists in Switzerland in regard to their orderliness, loyalty, and temporal rhythm. An inspection of types of careers and cohorts reveals that even if we face a decline of loyalty over time, hierarchical orderliness is not touched by those changes. Foremost, technical-industrial careers fit the loyal and regular pattern. Hence, this trajectory-type represents only a minority and is by far the slowest and least successful in terms of hierarchical ascension.

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

Structures and failure mechanisms analysis of Turtle Mountain

The 30 M m3 rockslide that occurred on the east face of Turtle Mountain in the Crowsnest Pass area (Alberta) in 1903 is one of the most famous landslides in the world. In this paper, the structural features of the South part of Turtle Mountain are investigated in order to understand the present-day scar morphology and to identify the most important failure mechanisms. The structural features were mapped using a high resolution digital elevation model (DEM) in order to have a large overview of the relevant structural features. At the same time, a field survey was carried out and small scale fractures were analyzed in different parts of southern Turtle Mountain in order to confirm the DEM analysis. Results allow to identify six main discontinuity sets that influence the Turtle Mountain morphology. These discontinuity sets were then used to identify the potential failure mechanisms affecting Third Peak and South Peak area.

Complex landslide behaviour and structural controlled by the structures: A 3D conceptual model example of Åknes rockslide, Norway

Åknes is an active complex large rockslide of approximately 30?40 Mm3 located within the Proterozoic gneisses of western Norway. The observed surface displacements indicate that this rockslide is divided into several blocks moving in different directions at velocities of between 3 and 10 cm year?1. Because of regional safety issues and economic interests this rockslide has been extensively monitored since 2004. The understanding of the deformation mechanism is crucial for the implementation of a viable monitoring system. Detailed field investigations and the analysis of a digital elevation model (DEM) indicate that the movements and the block geometry are controlled by the main schistosity (S1) in gneisses, folds, joints and regional faults. Such complex slope deformations use pre-existing structures, but also result in new failure surfaces and deformation zones, like preferential rupture in fold-hinge zones. Our interpretation provides a consistent conceptual three-dimensional (3D) model for the movements measured by various methods that is crucial for numerical stability modelling. In addition, this reinterpretation of the morphology confirms that in the past several rockslides occurred from the Åknes slope. They may be related to scars propagating along the vertical foliation in folds hinges. Finally, a model of the evolution of the Åknes slope is presented.

Anti-tumor necrosis factor drug survival in axial spondyloarthritis is independent of the classification criteria.

To compare the impact of meeting specific classification criteria [modified New York (mNY), European Spondyloarthropathy Study Group (ESSG), and Assessment of SpondyloArthritis international Society (ASAS) criteria] on anti-tumor necrosis factor (anti-TNF) drug retention, and to determine predictive factors of better drug survival. All patients fulfilling the ESSG criteria for axial spondyloarthritis (SpA) with available data on the axial ASAS and mNY criteria, and who had received at least one anti-TNF treatment were retrospectively retrieved in a single academic institution in Switzerland. Drug retention was computed using survival analysis (Kaplan-Meier), adjusted for potential confounders. Of the 137 patients classified as having axial SpA using the ESSG criteria, 112 also met the ASAS axial SpA criteria, and 77 fulfilled the mNY criteria. Drug retention rates at 12 and 24 months for the first biologic therapy were not significantly different between the diagnostic groups. Only the small ASAS non-classified axial SpA group (25 patients) showed a nonsignificant trend toward shorter drug survival. Elevated CRP level, but not the presence of bone marrow edema on magnetic resonance imaging (MRI) scans, was associated with significantly better drug retention (OR 7.9, ICR 4-14). In this cohort, anti-TNF drug survival was independent of the classification criteria. Elevated CRP level, but not positive MRI, was associated with better drug retention.

Health care supply, payment system and medical practice : evidence from obstetric practice

ABSTRACTA significant share of deliveries are performed by Cesarian section (C-section) in Europe and in many developed and developing countries. The aims of this thesis are to highlight the non medical, especially economic and financial, incentives that explain the use of C-section, as well as the medical consequences of C-section on women's health, in regard with other factors of ob¬stetrical care quality such as hospital concentration. Those diagnoses enable us to exhibit ways of improvement of obstetrical care quality in France. Our analysis focus on two countries, France and Switzerland. In the first part of the thesis, we show the influence of two non medical factors on the C-section use, namely the hospital payment system on the one hand and the obstetricians behaviour, especially their demand for leisure, on the other hand. With French data on the year 2003, we show firstly that the fee-for-service payment system of private for profit hospitals induces a higher probability of using C-section. Obstetricians play also a preeminent role in the decision to use a C-section, as the probability of a C-section rises with the number of obstetricians. We then focus on a French reform introduced in 2004, to investigate the impact of Prospective Payment System on obstetric practise. We show that the rise of C-section rate between 2003 and 2006 is mainly caused by changes in hospitals and patients features. Obstetricians practises do not vary a lot for patients with the same risk code. In the mean time however, the number of women coded with a high risk rises. This can be caused by improvements in the quality of coding, obstetricians chosing codes that match better the real health state of their patients. Yet, it can also show that obstetricians change their coding practises to justify the use of certain practises, such as C-section, with no regard to the health state of patients. Financial factors are not the only non medical fac¬tors that can influence the resort to C-section. Using Shelton Brown ΠΙ identification strategy, we focus on the potential impact of obstetricians leisure preference on the use of C-section. We use the distributions of days and hours of delivering and the types of C-section - planned or emergency C-sections - to show that the obstetricians demand for leisure has a significant impact on the resort to C-section, but only in emergency situations. The second part of the thesis deals with some ways to improve obstetric care quality. We use on the one hand swiss and french data to study the impact of C-section on the patients' probability of having an obstetric complication and on the other hand the influence of hospital concentration on the quality of obstetric care. We find the same results as former medical studies about the risks entailed by C-section on obstetric complications.These results prove women ought to be better informed of the medical consequences of C-section and that the slowing of C-section use should be a priority of public health policy. We finally focus on another way to improve obstetric care quality, that is hospital lmarket concentration. We investigate the impact of hospital concentration by integrating the Herfindahl-Hirschman index in our model, on health care quality, measured by the HCUP indicator. We find that hospital concentration has a negative impact on obstetric care quality, which undermines today's policy of hospital closings in France.JEL classification: 112; 118Keywords: Hospital; C-section; Payment System; Counterfactual Estimation; Quality of Care.RÉSUMÉUne part importante des accouchements sont réalisés par césarienne en Europe et dans de nom¬breux pays développés ou en développement. Les objectifs de cette thèse sont de mettre en évidence les déterminants non médicaux, notamment économiques et financiers, expliquant le développe¬ment de cette pratique, ainsi que ses conséquences sur la santé des femmes après Γ accouchement, en lien avec d'autres facteurs comme la concentration locale des structures hospitalières. Les résul¬tats exposés dans cette thèse éclairent les perspectives et voies d'amélioration de la qualité des soins en obstétriques.Notre analyse se concentre sur deux pays : la France et la Suisse. Dans la première partie de la thèse, nous mettons en évidence l'influence de deux déterminants non médicaux sur l'emploi de la césarienne : le système de paiement des hôpitaux d'une part, et le comportement des médecins obstétriciens d'autre part. En étudiant des données françaises de 2003, nous montrons d'abord que le financement à l'acte des établissements privés engendre une hausse de la proba¬bilité de pratiquer une césarienne. Le rôle de l'obstrétricien paraît également déterminant dans la décision d'opérer une césarienne, la probabilité d'employer cette technique augmentant avec le nombre d'obstétriciens. Nous nous intéressons ensuite à l'impact de la mise en place en 2004 du système de paiement prospectif sur l'évolution des pratiques obstétricales entre 2003 et 2006 en France. La hausse du taux de recours à la césarienne entre 2004 et 2006 peut ainsi être principa¬lement imputée aux évolutions des caractéristiques des hôpitaux et des patients, les pratiques des obstétriciens, pour un même codage de la situation du patient, variant peu. Dans le même temps cependant, les pratiques de codage des patients parles obstétriciens évoluent fortement, les femmes étant de plus en plus nombreuses à porter des codes correspondant à des situations à risques. Cette évolution peut indiquer que la qualité du codage en 2006 s'est améliorée par rapport à 2004, le codage correspondant de plus en plus à la situation réelle des patientes. H peut aussi indiquer que les pratiques de codage évoluent pour justifier un recours accru à la césarienne, sans lien avec l'état réel des patientes. Les facteurs financiers ne sont pas les seuls facteurs non médicaux à pouvoir expliquer le recours à la césarienne : nous nous intéressons, en suivant la stratégie d'identifica¬tion de Shelton Brown m, à l'impact potentiel de la demande de loisir des médecins obstétriciens sur la pratique de la césarienne. En utilisant la distribution des jours et heures d'accouchement, et en distinguant les césariennes planifiées de celles effectuées en urgence, nous constatons que la demande de loisir des obstétriciens influence significativement le recours à la césarienne, mais uni¬quement pour les interventions d'urgence. La deuxième partie de la thèse est consacrée à l'étude de la qualité des soins en obstétriques. Nous utilisons des données suisses et françaises pour analyser d'une part l'impact de la césarienne sur la survenue de complications obstétricales et d'autre part l'impact de la concentration des soins sur la qualité des soins en obstétrique. Nons confirmons les résultats antérieurs de la littérature médicale sur la dangerosité de la césarienne comme facteur de complications obstétricales. Ces conclusions montrent que les femmes ont besoin d'être informées des conséquences de la césarienne sur leur santé et que le ralentissement de l'augmentation de la pratique de la césarienne devrait être un objectif de la politique publique de santé. Nous nous in¬téressons à un autre facteur d'amélioration des soins en obstrétique, l'organisation des hôpitaux et particulièrement leur concentration. Nous estimons ainsi l'effet de la concentration sur la qualité des soins obstétriques en intégrant l'indice de Herfindahl-Hirschman dans notre modèle, la qualité des soins étant mesurée à l'aide de l'indicateur HCUP. Nous constatons que la concentration des naissances a un impact négatif sur la qualité des soins en obstétrique, résultat qui va dans le sens contraire des politiques de fermeture d'hôpitaux menées actuellement en France. JEL classification : 112 ; 118Mots-clés : Hôpital ; Césarienne ; Système de paiement ; Contrefactuels ; Qualité des soins, sur la qualité des soins en obstétrique.

The application of chemometrics on Infrared and Raman spectra as a tool for the forensic analysis of paints

The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm−1 and 2730-3600 cm−1, provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

A novel tool for the assessment of pain: validation in low back pain.

BACKGROUND: Adequate pain assessment is critical for evaluating the efficacy of analgesic treatment in clinical practice and during the development of new therapies. Yet the currently used scores of global pain intensity fail to reflect the diversity of pain manifestations and the complexity of underlying biological mechanisms. We have developed a tool for a standardized assessment of pain-related symptoms and signs that differentiates pain phenotypes independent of etiology. METHODS AND FINDINGS: Using a structured interview (16 questions) and a standardized bedside examination (23 tests), we prospectively assessed symptoms and signs in 130 patients with peripheral neuropathic pain caused by diabetic polyneuropathy, postherpetic neuralgia, or radicular low back pain (LBP), and in 57 patients with non-neuropathic (axial) LBP. A hierarchical cluster analysis revealed distinct association patterns of symptoms and signs (pain subtypes) that characterized six subgroups of patients with neuropathic pain and two subgroups of patients with non-neuropathic pain. Using a classification tree analysis, we identified the most discriminatory assessment items for the identification of pain subtypes. We combined these six interview questions and ten physical tests in a pain assessment tool that we named Standardized Evaluation of Pain (StEP). We validated StEP for the distinction between radicular and axial LBP in an independent group of 137 patients. StEP identified patients with radicular pain with high sensitivity (92%; 95% confidence interval [CI] 83%-97%) and specificity (97%; 95% CI 89%-100%). The diagnostic accuracy of StEP exceeded that of a dedicated screening tool for neuropathic pain and spinal magnetic resonance imaging. In addition, we were able to reproduce subtypes of radicular and axial LBP, underscoring the utility of StEP for discerning distinct constellations of symptoms and signs. CONCLUSIONS: We present a novel method of identifying pain subtypes that we believe reflect underlying pain mechanisms. We demonstrate that this new approach to pain assessment helps separate radicular from axial back pain. Beyond diagnostic utility, a standardized differentiation of pain subtypes that is independent of disease etiology may offer a unique opportunity to improve targeted analgesic treatment.

Segmentation of brain structures in presence of a space-occupying lesion.

Brain deformations induced by space-occupying lesions may result in unpredictable position and shape of functionally important brain structures. The aim of this study is to propose a method for segmentation of brain structures by deformation of a segmented brain atlas in presence of a space-occupying lesion. Our approach is based on an a priori model of lesion growth (MLG) that assumes radial expansion from a seeding point and involves three steps: first, an affine registration bringing the atlas and the patient into global correspondence; then, the seeding of a synthetic tumor into the brain atlas providing a template for the lesion; finally, the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. The method was applied on two meningiomas inducing a pure displacement of the underlying brain structures, and segmentation accuracy of ventricles and basal ganglia was assessed. Results show that the segmented structures were consistent with the patient's anatomy and that the deformation accuracy of surrounding brain structures was highly dependent on the accurate placement of the tumor seeding point. Further improvements of the method will optimize the segmentation accuracy. Visualization of brain structures provides useful information for therapeutic consideration of space-occupying lesions, including surgical, radiosurgical, and radiotherapeutic planning, in order to increase treatment efficiency and prevent neurological damage.

The use of classification and regression trees to predict the likelihood of seasonal influenza.

Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.