Naive possibilistic classifiers for imprecise or uncertain numerical data

International audienceIn real-world problems, input data may be pervaded with uncertainty. In this paper, we investigate the behavior of naive possibilistic classifiers, as a counterpart to naive Bayesian ones, for dealing with classification tasks in the presence of uncertainty. For this purpose, we extend possibilistic classifiers, which have been recently adapted to numerical data, in order to cope with uncertainty in data representation. Here the possibility distributions that are used are supposed to encode the family of Gaussian probabilistic distributions that are compatible with the considered dataset. We consider two types of uncertainty: (i) the uncertainty associated with the class in the training set, which is modeled by a possibility distribution over class labels, and (ii) the imprecision pervading attribute values in the testing set represented under the form of intervals for continuous data. Moreover, the approach takes into account the uncertainty about the estimation of the Gaussian distribution parameters due to the limited amount of data available. We first adapt the possibilistic classification model, previously proposed for the certain case, in order to accommodate the uncertainty about class labels. Then, we propose an algorithm based on the extension principle to deal with imprecise attribute values. The experiments reported show the interest of possibilistic classifiers for handling uncertainty in data. In particular, the probability-to-possibility transform-based classifier shows a robust behavior when dealing with imperfect data

Possibilistic classifiers for numerical data

International audienceNaive Bayesian Classifiers, which rely on independence hypotheses, together with a normality assumption to estimate densities for numerical data, are known for their simplicity and their effectiveness. However, estimating densities, even under the normality assumption, may be problematic in case of poor data. In such a situation, possibility distributions may provide a more faithful representation of these data. Naive Possibilistic Classifiers (NPC), based on possibility theory, have been recently proposed as a counterpart of Bayesian classifiers to deal with classification tasks. There are only few works that treat possibilistic classification and most of existing NPC deal only with categorical attributes. This work focuses on the estimation of possibility distributions for continuous data. In this paper we investigate two kinds of possibilistic classifiers. The first one is derived from classical or flexible Bayesian classifiers by applying a probability–possibility transformation to Gaussian distributions, which introduces some further tolerance in the description of classes. The second one is based on a direct interpretation of data in possibilistic formats that exploit an idea of proximity between data values in different ways, which provides a less constrained representation of them. We show that possibilistic classifiers have a better capability to detect new instances for which the classification is ambiguous than Bayesian classifiers, where probabilities may be poorly estimated and illusorily precise. Moreover, we propose, in this case, an hybrid possibilistic classification approach based on a nearest-neighbour heuristics to improve the accuracy of the proposed possibilistic classifiers when the available information is insufficient to choose between classes. Possibilistic classifiers are compared with classical or flexible Bayesian classifiers on a collection of benchmarks databases. The experiments reported show the interest of possibilistic classifiers. In particular, flexible possibilistic classifiers perform well for data agreeing with the normality assumption, while proximity-based possibilistic classifiers outperform others in the other cases. The hybrid possibilistic classification exhibits a good ability for improving accuracy

Professional quality of life and burnout amongst radiation oncologists:The impact of alexithymia and empathy

Background and purpose: Different factors may influence the professional quality of life of oncology professionals. Among them, personality traits, as alexithymia and empathy, are underinvestigated. Alexithymia is about deficits in emotion processing and awareness. Empathy is the ability to understand another's 'state of mind'/emotion. The PROject on BurnOut in RadiatioN Oncology (PRO BONO) assesses professional quality of life, including burnout, in the field of radiation oncology and investigates alexithymia and empathy as contributing factors. Material and methods: An online survey was conducted amongst ESTRO members. Participants completed 3 validated questionnaires for alexithymia, empathy and professional quality of life: (a) Toronto Alexithymia Scale; (b) Interpersonal Reactivity Index; (c) Professional Quality of Life Scale. The present analysis, focusing on radiation/clinical oncologists, evaluates Compassion Satisfaction (CS), Secondary Traumatic Stress (STS) and Burnout and correlates them with alexithymia and empathy (empathic concern, perspective taking and personal distress) with generalized linear modeling. Significant covariates on univariate linear regression analysis were included in the multivariate linear regression model. Results: A total of 825 radiation oncologists completed all questionnaires. A higher level of alexithymia was associated to decreased CS (beta:-0.101; SE: 0.018; p <0.001), increased STS (beta: 0.228; SE: 0.018; p <0.001) and burnout (beta: 0.177; SE: 0.016; p <0.001). A higher empathic concern was significantly associated to increased CS (beta: 0.1.287; SE: 0.305; p = 0.001), STS (beta: 0.114; SE: 0.296; p <0.001), with no effect on burnout. Personal distress was associated to decreased CS (beta:-1.423; SE: 0.275; p <0.001), increased STS (beta: 1.871; SE: 0.283; p <0.001) and burnout (beta: 1.504; SE: 0.245; p <0.001). Conclusions: Alexithymic personality trait increased burnout risk, with less professional satisfaction. Empathic concern was associated to increased stress, without leading to burnout, resulting in higher professional fulfillment. These results may be used to benchmark preventing strategies, such as work-hour restrictions, peer support, debriefing sessions, and leadership initiatives for professionals at risk. (c) 2020 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 147 (2020) 162-16

Evaluation de la stratégie de lutte contre le cancer en Suisse, Phase 2, 2002 : document de synthèse

[Table des matières] 1. Introduction. 2. Méthode. 3. Conclusions et recommandations générales. 3.1. Stratégie. 3.2. Conclusions et recommandations concernant la stratégie, les structures et le fonctionnement, la collaboration avec l'extérieur. 3.3. Les 4 programmes nationaux. 3.4. Conclusions et recommandations pour les 4 programmes nationaux. 3.5. Bilan de l'expérience de la mise en place du dépistage du sein. 3.6. Conclusions et recommandations pour la mise en place du dépistage du sein. 3.7. Les données à disposition pour le suivi et l'évaluation de la stratégie nationale de lutte contre le cancer. 3.8. Conclusions et recommandations pour le suivi et l'évaluation de la stratégie nationale de lutte contre le cancer. 4. Annexes: Résumés des études 1 à 7. Etude 1: Suivi du développement de la stratégie nationale. Studie 2: Prozessevaluation und Prozessdokumentation. Studie 3: Mammographie-Screening in der Schweiz : eine retrospektive Analyse zur Umsetzung. Studie 4: Sekundäre Analyse der verfügbaren Indikatoren zur Messung der Ergebnisse des nationalen Krebsbekämpfungsprogrammes. Etude 5: Quel ancrage local des actions de la Ligue suisse contre le cancer ? : l'exemple de la prévention du mélanome. Studie 6: Begleitevaluation der Pilotphase des Aktionsmonats Brustkrebs. Etude 7: Accompagnement psychosocial des personnes ayant un diagnostic de cancer : étude de deux cantons

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Excessive Food Intake, Obesity and Inflammation Process in Zucker fa/fa Rat Pancreatic Islets

Inappropriate food intake-related obesity and more importantly, visceral adiposity, are major risk factors for the onset of type 2 diabetes. Evidence is emerging that nutriment-induced β-cell dysfunction could be related to indirect induction of a state of low grade inflammation. Our aim was to study whether hyperphagia associated obesity could promote an inflammatory response in pancreatic islets leading to ß-cell dysfunction. In the hyperphagic obese insulin resistant male Zucker rat, we measured the level of circulating pro-inflammatory cytokines and estimated their production as well as the expression of their receptors in pancreatic tissue and β-cells. Our main findings concern intra-islet pro-inflammatory cytokines from fa/fa rats: IL-1β, IL-6 and TNFα expressions were increased; IL-1R1 was also over-expressed with a cellular redistribution also observed for IL-6R. To get insight into the mechanisms involved in phenotypic alterations, abArrays were used to determine the expression profile of proteins implicated in different membrane receptors signaling, apoptosis and cell cycle pathways. Despite JNK overexpression, cell viability was unaffected probably because of decreases in cleaved caspase3 as well as in SMAC/DIABLO and APP, involved in the induction and amplification of apoptosis. Concerning β-cell proliferation, decreases in important cell cycle regulators (Cyclin D1, p35) and increased expression of SMAD4 probably contribute to counteract and restrain hyperplasia in fa/fa rat islets. Finally and probably as a result of IL-1β and IL-1R1 increased expressions with sub-cellular redistribution of the receptor, islets from fa/fa rats were found more sensitive to both stimulating and inhibitory concentrations of the cytokine; this confers some physiopathological relevance to a possible autocrine regulation of β-cell function by IL-1β. These results support the hypothesis that pancreatic islets from prediabetic fa/fa rats undergo an inflammatory process. That the latter could contribute to β-cell hyperactivity/proliferation and possibly lead to progressive β-cell failure in these animals, deserves further investigations

Standardization of in vitro digestibility and DIAAS method based on the static INFOGEST protocol

Background: The FAO recommends the digestible indispensable amino acid score (DIAAS) as the measure for protein quality, for which the true ileal digestibility needs to be assessed in humans or pigs. However, due to high costs and ethical concerns, the FAO strongly encourages as well the development of validated in vitro methods, which complement the in vivo experiments. Method: Recently, an in vitro workflow, based on the validated static INFOGEST protocol, was developed and compared towards in vivo data. In parallel to the validation with in vivo data, the repeatability and reproducibility of the in vitro protocol were tested in an international ring trial (RT) with the aim to establish an international ISO standard method within the International Dairy Federation (IDF). Five different dairy products (skim milk powder, whole milk powder, whey protein isolate, yoghurt, and cheese) were analyzed in 32 different laboratories from 18 different countries, across 4 continents. Results: in vitro protein digestibilities based on Nitrogen, free R-NH2, and total amino acids as well as DIAAS values were calculated and compared to in vivo data, where available. Conclusion: The in vitro method is suited for quantification of digestibility and will be further implemented to other food matricesinfo:eu-repo/semantics/publishedVersio