How are "teaching the teachers" courses in evidence based medicine evaluated? A systematic review.

BACKGROUND: Teaching of evidence-based medicine (EBM) has become widespread in medical education. Teaching the teachers (TTT) courses address the increased teaching demand and the need to improve effectiveness of EBM teaching. We conducted a systematic review of assessment tools for EBM TTT courses.To summarise and appraise existing assessment methods for teaching the teachers courses in EBM by a systematic review. METHODS: We searched PubMed, BioMed, EmBase, Cochrane and Eric databases without language restrictions and included articles that assessed its participants. Study selection and data extraction were conducted independently by two reviewers. RESULTS: Of 1230 potentially relevant studies, five papers met the selection criteria. There were no specific assessment tools for evaluating effectiveness of EBM TTT courses. Some of the material available might be useful in initiating the development of such an assessment tool. CONCLUSION: There is a need for the development of educationally sound assessment tools for teaching the teachers courses in EBM, without which it would be impossible to ascertain if such courses have the desired effect.

Online teaching of inflammatory skin pathology by a French-speaking International University Network

INTRODUCTION: Developments in technology, web-based teaching and whole slide imaging have broadened the teaching horizon in anatomic pathology. Creating online learning material including many types of media such as radiologic images, whole slides, videos, clinical and macroscopic photographs, is now accessible to most universities. Unfortunately, a major limiting factor to maintain and update the learning material is the amount of resources needed. In this perspective, a French-national university network was initiated in 2011 to build joint online teaching modules consisting of clinical cases and tests. The network has since expanded internationally to Québec, Switzerland and Ivory Coast. METHOD: One of the first steps of the project was to build a learning module on inflammatory skin pathology for interns and residents in pathology and dermatology. A pathology resident from Québec spent 6 weeks in France and Switzerland to develop the contents and build the module on an e-learning Moodle platform under the supervision of two dermatopathologists. The learning module contains text, interactive clinical cases, tests with feedback, virtual slides, images and clinical photographs. For that module, the virtual slides are decentralized in 2 universities (Bordeaux and Paris 7). Each university is responsible of its own slide scanning, image storage and online display with virtual slide viewers. RESULTS: The module on inflammatory skin pathology includes more than 50 web pages with French original content, tests and clinical cases, links to over 45 virtual images and more than 50 microscopic and clinical photographs. The whole learning module is being revised by four dermatopathologists and two senior pathologists. It will be accessible to interns and residents in the spring of 2014. The experience and knowledge gained from that work will be transferred to the next international resident whose work will be aimed at creating lung and breast pathology learning modules. CONCLUSION: The challenges of sustaining a project of this scope are numerous. The technical aspect of whole-slide imaging and storage needs to be developed by each university or group. The content needs to be regularly updated and its accuracy reviewed by experts in each individual domain. The learning modules also need to be promoted within the academic community to ensure maximal benefit for trainees. A collateral benefit of the project was the establishment of international partnerships between French-speaking universities and pathologists with the common goal of promoting pathology education through the use of multi-media technology including whole slide imaging.

Online teaching of inflammatory skin pathology by a French-speaking International University Network.

INTRODUCTION: Developments in technology, web-based teaching and whole slide imaging have broadened the teaching horizon in anatomic pathology. Creating online learning material including many types of media such as radiologic images, whole slides, videos, clinical and macroscopic photographs, is now accessible to most universities. Unfortunately, a major limiting factor to maintain and update the learning material is the amount of resources needed. In this perspective, a French-national university network was initiated in 2011 to build joint online teaching modules consisting of clinical cases and tests. The network has since expanded internationally to Québec, Switzerland and Ivory Coast. METHOD: One of the first steps of the project was to build a learning module on inflammatory skin pathology for interns and residents in pathology and dermatology. A pathology resident from Québec spent 6 weeks in France and Switzerland to develop the contents and build the module on an e-learning Moodle platform under the supervision of two dermatopathologists. The learning module contains text, interactive clinical cases, tests with feedback, virtual slides, images and clinical photographs. For that module, the virtual slides are decentralized in 2 universities (Bordeaux and Paris 7). Each university is responsible of its own slide scanning, image storage and online display with virtual slide viewers. RESULTS: The module on inflammatory skin pathology includes more than 50 web pages with French original content, tests and clinical cases, links to over 45 virtual images and more than 50 microscopic and clinical photographs. The whole learning module is being revised by four dermatopathologists and two senior pathologists. It will be accessible to interns and residents in the spring of 2014. The experience and knowledge gained from that work will be transferred to the next international resident whose work will be aimed at creating lung and breast pathology learning modules. CONCLUSION: The challenges of sustaining a project of this scope are numerous. The technical aspect of whole-slide imaging and storage needs to be developed by each university or group. The content needs to be regularly updated and its accuracy reviewed by experts in each individual domain. The learning modules also need to be promoted within the academic community to ensure maximal benefit for trainees. A collateral benefit of the project was the establishment of international partnerships between French-speaking universities and pathologists with the common goal of promoting pathology education through the use of multi-media technology including whole slide imaging.

Study design for technology assessment: critical issues.

The epidemiological methods have become useful tools for the assessment of the effectiveness and safety of health care technologies. The experimental methods, namely the randomized controlled trials (RCT), give the best evidence of the effect of a technology. However, the ethical issues and the very nature of the intervention under study sometimes make it difficult to carry out an RCT. Therefore, quasi-experimental and non-experimental study designs are also applied. The critical issues concerning these designs are discussed. The results of evaluative studies are of importance for decision-makers in health policy. The measurements of the impact of a medical technology should go beyond a statement of its effectiveness, because the essential outcome of an intervention or programme is the health status and quality of life of the individuals and populations concerned.

Gamma Knife, CyberKnife, TomoTherapy: gadgets or useful tools?

Purpose of reviewThis review provides information and an update on stereotactic radiosurgery (SRS) equipment, with a focus on intracranial lesions and brain neoplasms.Recent findingsGamma Knife radiosurgery represents the gold standard for intracranial radiosurgery, using a dedicated equipment, and has recently evolved with a newly designed technology, Leksell Gamma Knife Perfexion. Linear accelerator-based radiosurgery is more recent, and originally based on existing systems, either adapted or dedicated to radiosurgery. Equipment incorporating specific technologies, such as the robotic CyberKnife system, has been developed. Novel concepts in radiation therapy delivery techniques, such as intensity-modulated radiotherapy, were also developed; their integration with computed tomography imaging and helical delivery has led to the TomoTherapy system. Recent data on the management of intracranial tumors with radiosurgery illustrate the trend toward a larger use and acceptance of this therapeutic modality.SummarySRS has become an important alternative treatment for a variety of lesions. Each radiosurgery system has its advantages and limitations. The 'perfect' and ubiquitous system does not exist. The choice of a radiosurgery system may vary with the strategy and needs of specific radiosurgery programs. No center can afford to acquire every technology, and strategic choices have to be made. Institutions with large neurosurgery and radiation oncology programs usually have more than one system, allowing optimization of the management of patients with a choice of open neurosurgery, radiosurgery, and radiotherapy. Given its minimally invasive nature and increasing clinical acceptance, SRS will continue to progress and offer new advances as a therapeutic tool in neurosurgery and radiotherapy.

Conceptual models for designing information systems supporting the strategic analysis of technology environments

1 6 STRUCTURE OF THIS THESIS -Chapter I presents the motivations of this dissertation by illustrating two gaps in the current body of knowledge that are worth filling, describes the research problem addressed by this thesis and presents the research methodology used to achieve this goal. -Chapter 2 shows a review of the existing literature showing that environment analysis is a vital strategic task, that it shall be supported by adapted information systems, and that there is thus a need for developing a conceptual model of the environment that provides a reference framework for better integrating the various existing methods and a more formal definition of the various aspect to support the development of suitable tools. -Chapter 3 proposes a conceptual model that specifies the various enviromnental aspects that are relevant for strategic decision making, how they relate to each other, and ,defines them in a more formal way that is more suited for information systems development. -Chapter 4 is dedicated to the evaluation of the proposed model on the basis of its application to a concrete environment to evaluate its suitability to describe the current conditions and potential evolution of a real environment and get an idea of its usefulness. -Chapter 5 goes a step further by assembling a toolbox describing a set of methods that can be used to analyze the various environmental aspects put forward by the model and by providing more detailed specifications for a number of them to show how our model can be used to facilitate their implementation as software tools. -Chapter 6 describes a prototype of a strategic decision support tool that allow the analysis of some of the aspects of the environment that are not well supported by existing tools and namely to analyze the relationship between multiple actors and issues. The usefulness of this prototype is evaluated on the basis of its application to a concrete environment. -Chapter 7 finally concludes this thesis by making a summary of its various contributions and by proposing further interesting research directions.

Coevolution of adaptive technology, maladaptive culture and population size in a producer-scrounger game.

Technology (i.e. tools, methods of cultivation and domestication, systems of construction and appropriation, machines) has increased the vital rates of humans, and is one of the defining features of the transition from Malthusian ecological stagnation to a potentially perpetual rising population growth. Maladaptations, on the other hand, encompass behaviours, customs and practices that decrease the vital rates of individuals. Technology and maladaptations are part of the total stock of culture carried by the individuals in a population. Here, we develop a quantitative model for the coevolution of cumulative adaptive technology and maladaptive culture in a 'producer-scrounger' game, which can also usefully be interpreted as an 'individual-social' learner interaction. Producers (individual learners) are assumed to invent new adaptations and maladaptations by trial-and-error learning, insight or deduction, and they pay the cost of innovation. Scroungers (social learners) are assumed to copy or imitate (cultural transmission) both the adaptations and maladaptations generated by producers. We show that the coevolutionary dynamics of producers and scroungers in the presence of cultural transmission can have a variety of effects on population carrying capacity. From stable polymorphism, where scroungers bring an advantage to the population (increase in carrying capacity), to periodic cycling, where scroungers decrease carrying capacity, we find that selection-driven cultural innovation and transmission may send a population on the path of indefinite growth or to extinction.

'Bio-nano interactions: new tools, insights and impacts': summary of the Royal Society discussion meeting

Bio-nano interactions can be defined as the study of interactions between nanoscale entities and biological systems such as, but not limited to, peptides, proteins, lipids, DNA and other biomolecules, cells and cellular receptors and organisms including humans. Studying bio-nano interactions is particularly useful for understanding engineered materials that have at least one dimension in the nanoscale. Such materials may consist of discrete particles or nanostructured surfaces. Much of biology functions at the nanoscale; therefore, our ability to manipulate materials such that they are taken up at the nanoscale, and engage biological machinery in a designed and purposeful manner, opens new vistas for more efficient diagnostics, therapeutics (treatments) and tissue regeneration, so-called nanomedicine. Additionally, this ability of nanomaterials to interact with and be taken up by cells allows nanomaterials to be used as probes and tools to advance our understanding of cellular functioning. Yet, as a new technology, assessment of the safety of nanomaterials, and the applicability of existing regulatory frameworks for nanomaterials must be investigated in parallel with development of novel applications. The Royal Society meeting 'Bio-nano interactions: new tools, insights and impacts' provided an important platform for open dialogue on the current state of knowledge on these issues, bringing together scientists, industry, regulatory and legal experts to concretize existing discourse in science law and policy. This paper summarizes these discussions and the insights that emerged.

New genetic models and mesenchymal cells as tools to ameliorate anti-tumor immunity

Résumé Le but final de ce projet est d'utiliser des cellules T ou des cellules souches mésenchymateuses modifiées génétiquement afin de surexprimer localement les deux chémokines CXCL13 et CCL2 ensemble ou chacune séparément à l'intérieur d'une tumeur solide. CXCL13 est supposé induire des structures lymphoïdes ectopiques. Un niveau élevé de CCL2 est présumé initier une inflammation aiguë. La combinaison des deux effets amène à un nouveau modèle d'étude des mécanismes régulateur de la tolérance périphérique et de l'immunité tumorale. Les connaissances acquises grâce à ce modèle pourraient permettre le développement ou l'amélioration des thérapies immunes du cancer. Le but premier de ce travail a été l'établissement d'un modèle génétique de la souris permettant d'exprimer spécifiquement dans la tumeur les deux chémokines d'intérêt à des niveaux élevés. Pour accomplir cette tâche, qui est en fait une thérapie génétique de tumeurs solides, deux types de cellules porteuses potentielles ont été évaluées. Des cellules CD8+ T et des cellules mésenchymateuses de la moelle osseuse transférées dans des receveurs portant une tumeur. Si on pouvait répondre aux besoins de la thérapie génétique, indépendamment de la thérapie immune envisagée, on posséderait là un outil précieux pour bien d'autres approches thérapeutiques. Plusieurs lignées de souris transgéniques ont été générées comme source de cellules CD8+ T modifiées afin d'exprimer les chémokines d'intérêt. Dans une approche doublement transgénique les propriétés de deux promoteurs spécifiques de cellules T ont été combinées en utilisant la technologie Cre-loxP. Le promoteur de granzyme B confère une dépendance d'activation et le promoteur distal de lck assure une forte expression constitutive dès que les cellules CD8+ T ont été activées. Les transgènes construits ont montré une bonne performance in vivo et des souris qui expriment CCL2 dans des cellules CD8+ T activées ont été obtenues. Ces cellules peuvent maintenant être utilisées avec différents protocoles pour transférer des cellules T cytotoxiques (CTL) dans des receveurs porteur d'une tumeur, permettant ainsi d'évaluer leur capacité en tant que porteuse de chémokine d'infiltrer la tumeur. L'établissement de souris transgéniques, qui expriment pareillement CXCL13 est prévu dans un avenir proche. L'évaluation de cellules mésenchymateuses de la moelle osseuse a démontré que ces cellules se greffent efficacement dans le stroma tumoral suite à la co-injection avec des cellules tumorales. Cela représente un outil précieux pour la recherche, vu qu'il permet d'introduire des cellules manipulées dans un modèle tumoral. Les résultats confirment partiellement d'autres résultats rapportés dans un modèle amélioré. Cependant, l'efficacité et la spécificité suggérées de la migration systémique de cellules mésenchymateuses de la moelle osseuse dans une tumeur n'ont pas été observées dans notre modèle, ce qui indique, que ces cellules ne se prêtent pas à une utilisation thérapeutique. Un autre résultat majeur de ce travail est l'établissement de cultures de cellules mésenchymateuses de la moelle osseuse in vitro conditionnées par des tumeurs, ce qui a permis à ces cellules de s'étendre plus rapidement en gardant leur capacité de migration et de greffe. Cela offre un autre outil précieux, vu que la culture in vitro est un pas nécessaire pour une manipulation thérapeutique. Abstract The ultimate aim of the presented project is to use genetically modified T cells or mesenchymal stem cells to locally overexpress the two chemokines CXCL13 and CCL2 together or each one alone inside a solid tumor. CXCL13 is supposed to induce ectopic lymphoid structures and a high level of CCL2 is intended to trigger acute inflamation. The combination of these two effects represents a new model for studying mechanisms that regulate peripheral tolerance and tumor immunity. Gained insights may help developing or improving immunotherapy of cancer. The primary goal of the executed work was the establishment of a genetic mouse model that allows tumor-specific expression of high levels of the two chemokines of interest. For accomplishing this task, which represents gene therapy of solid tumors, two types of potentially useful carrier cells were evaluated. CD8+ T cells and mesenchymal bone marrow cells to be used in adoptive cell transfers into tumor-bearing mice. Irrespectively of the envisaged immunotherapy, satisfaction of so far unmet needs of gene therapy would be a highly valuable tool that may be employed by many other therapeutic approaches, too. Several transgenic mouse lines were generated as a source of CD8+ T cells modified to express the chemokines of interest. In a double transgenic approach the properties of two T cell-specific promoters were combined using Cre-loxP technology. The granzyme B promoter confers activation-dependency and the lck distal promoter assures strong constitutive expression once the CD8+ T cell has been activated. The constructed transgenes showed a good performance in vivo and mice expressing CCL2 in activated CD8+ T cells were obtained. These cells can now be used with different protocols for adoptively transferring cytotoxic T cells (CTL) into tumor-bearing recipients, thus allowing to study their capacity as tumor-infiltrating chemokine carrier. The establishment of transgenic mice likewisely expressing CXCL13 is expected in the near future. In addition, T cells from generated single transgenic mice that have high expression of an EGFP reporter in both CD4+ and CD8+ cells can be easily traced in vivo when setting up adoptive transfer conditions. The evaluation of mesenchymal bone marrow cells demonstrated that these cells can efficiently engraft into tumor stroma upon local coinjection with tumor cells. This represents a valuable tool for research purposes as it allows to introduce manipulated stromal cells into a tumor model. Therefore, the established engraftment model is suited for studying the envisaged immunotherapy. These results confirm to some extend previously reported results in an improved model, however, the suggested systemic tumor homing efficiency and specificity of mesenchymal bone marrow cells was not observed in our model indicating that these cells may not be suited for therapeutic use. Another major result of the presented work is the establishment oftumor-conditioned in vitro culture of mesenchymal bone marrow cells, which allowed to more rapidly expand these cells while maintaining their tumor homing and engrafting capacities. This offers another valuable tool as in vitro culture is a necessary step for therapeutic manipulations.

Tissue microarray and immunohistochemistry as tools for evaluation of antibodies against Chlamydia-like bacteria.

Tissue microarray technology was used to establish immunohistochemistry protocols and to determine the specificity of new antisera against various Chlamydia-like bacteria for future use on formalin-fixed and paraffin-embedded tissues. The antisera exhibited strong reactivity against autologous antigen and closely related heterologous antigen, but no cross-reactivity with distantly related species.

First insights into the transcriptome and development of new genomic tools of a widespread circum-Mediterranean tree species, Pinus halepensis Mill.

Aleppo pine (Pinus halepensis Mill.) is a relevant conifer species for studying adaptive responses to drought and fire regimes in the Mediterranean region. In this study, we performed Illumina next-generation sequencing of two phenotypically divergent Aleppo pine accessions with the aims of (i) characterizing the transcriptome through Illumina RNA-Seq on trees phenotypically divergent for adaptive traits linked to fire adaptation and drought, (ii) performing a functional annotation of the assembled transcriptome, (iii) identifying genes with accelerated evolutionary rates, (iv) studying the expression levels of the annotated genes and (v) developing gene-based markers for population genomic and association genetic studies. The assembled transcriptome consisted of 48,629 contigs and covered about 54.6 Mbp. The comparison of Aleppo pine transcripts to Picea sitchensis protein-coding sequences resulted in the detection of 34,014 SNPs across species, with a Ka /Ks average value of 0.216, suggesting that the majority of the assembled genes are under negative selection. Several genes were differentially expressed across the two pine accessions with contrasted phenotypes, including a glutathione-s-transferase, a cellulose synthase and a cobra-like protein. A large number of new markers (3334 amplifiable SSRs and 28,236 SNPs) have been identified which should facilitate future population genomics and association genetics in this species. A 384-SNP Oligo Pool Assay for genotyping with the Illumina VeraCode technology has been designed which showed an high overall SNP conversion rate (76.6%). Our results showed that Illumina next-generation sequencing is a valuable technology to obtain an extensive overview on whole transcriptomes of nonmodel species with large genomes.

MAR elements as tools to increase protein production by CHO cells

One of the major hurdles of isolating stable, inducible or constitutive high-level producer cell lines is the time-consuming selection, analysis and characterization of the numerous clones required to identify one with the desired characteristics. Various boundary elements, matrix attachment regions, and locus control regions were screened for for their ability to augment the expression of heterologous genes in CHO and other cells. The 5'-matrix-attachment region (MAR) of the chicken lysozyme gene was found to significantly increase stable gene expression, in culture dishes and in bioreactors. These MAR elements can be easily combined with various existing expression systems, as they can be added in trans (i.e. on a separate plasmid) in co-transfections with previously constructed expression vectors. Using cell population analysis, we found that the use of the MAR increases the proportion of high-producing CHO cell clones, thus reducing the number of cell lines that need to be screened while increasing maximal productivity. Random cDNA cloning and sequencing indicated that over 12% of the ESTs correspond to the transgene. Thus, productivity is no longer limited by transcriptional events in such MAR-containing cell lines. The identification of small and more convenient active MAR portions will also be summarized. Finally, we will show examples of how MAR elements can be combined with short term expression to increase the simultaneous synthesis of many proteins in parallel by CHO cells. Overall, we conclude that the MAR sequence is a versatile tool to increase protein expression in short and long term production processes.

Online teaching of inflammatory skin pathology by a French-speaking international university network

Introduction: Developments in technology, webbased teaching and whole slide imaging have broadened the teaching horizon in anatomic pathology. Creating online learning material including many types of media like radiologic images, videos, clinical and macroscopic photographs and whole slides imaging is now accessible to almost every university. Unfortunately, a major limiting factor to maintain and update the learning material is the amount of work, time and resources needed. In this perspective, a French national university network was initiated in 2011 to build mutualised online teaching pathology modules with clinical cases and tests. This network has been extended to an international level in 2012-2014 (Quebec, Switzerland and Ivory Coast). Method: One of the first steps of the international project was to build a learning module on inflammatory skin pathology intended for interns and residents of pathology and dermatology. A pathology resident from Quebec spent 6 weeks in France and Switzerland to develop the contents and build the module on an e-learning Moodle platform (http: //moodle.sorbonne-paris-cite.fr) under the supervision of two dermatopathologists (BV, MB). The learning module contains text, interactive clinical cases, tests with feedback, whole slides images (WSI), images and clinical photographs. For that module, the virtual slides are decentralized in 2 universities (Bordeaux and Paris 7). Each university is responsible of its own slide scanning, image storage and online display with virtual slide viewers. Results: The module on inflammatory skin pathology includes more than 50 web pages with French original content, tests and clinical cases, links to over 45 WSI and more than 50 micro and clinical photographs. The whole learning module is currently being revised by four dermatopathologists and two senior pathologists. It will be accessible to interns and residents in spring 2014. The experience and knowledge gained from that work will be transferred to the next international fellowship intern whose work will be aimed at creating lung and breast pathology learning modules. Conclusion: The challenges of sustaining a project of this scope are numerous. The technical aspect of whole-slide imaging and storage needs to be developed by each university or group. The content needs to be regularly updated, completed and its use and existence needs to be promoted by the different actors in pathology. Of the great benefits of that kind of project are the international partnerships and connections that have been established between numerous Frenchspeaking universities and pathologists with the common goals of promoting education in pathology and the use of technology including whole slide imaging. * The Moodle website is hosted by PRES Sorbonne Paris Cité, and financial supports for hardware have been obtained from UNF3S (http://www.unf3s.org/) and PRES Sorbonne Paris Cité. Financial support for international fellowships has been obtained from CFQCU (http://www.cfqcu.org/).

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.