biblio_i02.bib

@ARTICLE{rizzoli2002geographical,
  AUTHOR = {A. Rizzoli and S. Merler and C. Furlanello and C. Genchi},
  TITLE = {Geographical Information System and Bootstrap Aggregation (Bagging) of Tree-Based Classifiers for Lyme Disease Risk Prediction in Trentino, Italian Alps},
  JOURNAL = {Journal of Medical Entomology},
  YEAR = {2002},
  VOLUME = {39},
  NUMBER = {3},
  PAGES = {485-492},
  ABSTRACT = {The risk of exposure to Lyme disease in the province of Trento, Italian Alps, was predicted through the analysis of the distribution of Ixodes ricinus (L.) nymphs infected with Borrelia burgdorferi s.l. with a model based on bootstrap aggregation (bagging) of tree-based classifiers within a Geographical Information System. Data on I. ricinus density assessed by dragging the vegetation in 438 sites during 1996 were cross-correlated with the digital cartography of a GIS which included the variables altitude, exposure and slope, substratum, vegetation type and roe deer density. Ticks resulted more abundant at altitudes below 1,300 m a.s.l., in the presence of limestone and vegetation cover with thermophile deciduous forests with high densities of roe deer. A bootstrap aggregation procedure (bagging) was used to produce a model for the prediction of tick occurrence, which accuracy was tested on actual tick counts assessed by a further dragging campaign carried out during 1997 to determine infection prevalence and resulted in average 77\%. Other tests of the model were made on other additional and independent data set. The prevalence of infection with Borrelia burgdorferi s.l, determined by PCR on 2,208 nymphs collected by dragging the vegetation during 1997 in 245 transects selected randomly within 8 areas where I. ricinus was predicted to occur by the model, was 17.5\%  and was positively correlated to tick abundance and roe deer density. These findings were used to relate the output of the bagged model (probability of tick occurrence) to the density of infected nymphs through a stepwise model selection procedure and thus to produce a GIS digital map of the probability distribution of infected nymphs in the Province of Trento at high resolution scale (50 m$\times$ 50 m cell resolution).The application of the bagging procedure increased the accuracy of the prediction made by a single classification tree, a well known classification method for the analysis of epidemiological data.
},
  LINK = {http://mpa.itc.it/papers/rizzoli2002geographical.pdf}
}

@INBOOK{wilson2002theecology,
  AUTHOR = {K. Wilson and  O.N. Bjornstad and  A.P. Dobson and S. Merler and G. Poglayen and S.E. Randolph and A.F. Read and A. Skorping},
  EDITOR = {J. Hudson and A. Rizzoli and B.T. Grenfell and H. Heesterbeek and A. P. Dobson},
  TITLE = {The Ecology of Wildlife Diseases},
  CHAPTER = {Heterogeneities in macroparasite infections: patterns and processes},
  PUBLISHER = {Oxford University Press},
  YEAR = {2002},
  PAGES = {6-64}
}

@INBOOK{hess2002theecology,
  AUTHOR = {G.R. Hess and S.E. Randolph and P. Arneberg and C. Chemini and C. Furlanello and J. Harwood and M. Roberts and J. Swinton},
  EDITOR = {J. Hudson and A. Rizzoli and B.T. Grenfell and H. Heesterbeek and A. P. Dobson},
  TITLE = {The Ecology of Wildlife Diseases},
  CHAPTER = {Spatial aspects of disease dynamics},
  PUBLISHER = {Oxford University Press},
  YEAR = {2002},
  PAGES = {102-118}
}

@ARTICLE{furlanello2002webgis,
  AUTHOR = {C. Furlanello and S. Merler and S. Menegon and S. Mancuso and G. Bertiato},
  TITLE = {New {WEBGIS} technologies for geolocation of epidemiological data: an application for the surveillance of the risk of {L}yme borrelliosis disease},
  JOURNAL = {Giornale Italiano di Aritmologia e Cardiostimolazione},
  YEAR = {2002},
  VOLUME = {5},
  NUMBER = {1},
  PAGES = {241--245},
  ABSTRACT = {We present a technology for the accurate and fast
 geo-location of medical data and the creation of central data
 archives, specifically designed for the development of disease risk
 maps and of other functions for modern epidemiology and
 surveillance. A WEBGIS system is configured as an Internet web
 service integrated with connectivity to a Geographical Information
 System (GIS). We developed for the ULSS Belluno a WEBGIS for the
 accurate mapping of tick-borne diseases, with specific attention to
 Lyme borreliosis, which may cause cardiac manifestations as
 atrioventricular conduction abnormalities, complete atrioventricular
 block, myocarditis and dilated cardiomiopathy. A first tree-based
 predictive model has been developed for risk classification of tick
 bites from 256 samples (data gathered through the Belluno Lyme
 WEBGIS), with a descriptive error of 81.9\% and a predictive error of 75.1\% . An experimental risk GIS map was therefore
 obtained from the model by considering altitude, week of sampling and
 vegetation type as predictor variables.},
  LINK = {http://mpa.itc.it/papers/furlanello2002webgis.pdf}
}

@INPROCEEDINGS{caprile2002highlighting,
  AUTHOR = {B. Caprile and C. Furlanello and S. Merler},
  TITLE = {Highlighting Hard Patterns via {A}daBoost Weights Evolution},
  YEAR = {2002},
  BOOKTITLE = {Multiple  Classifier Systems, Lecture Notes in Computer Science 2364},
  PUBLISHER = {Springer},
  EDITOR = {J. Kittler and F. Roli},
  PAGES = {72-80},
  ABSTRACT = {The dynamical evolution of weights in the Adaboost
algorithm contains useful information about the r{\^o}le that the
associated data points play in the built of the Adaboost model. In
particular, the dynamics induces a bipartition of the data set into
two (easy/hard) classes. Easy points are ininfluential in the making
of the model, while the varying relevance of hard points can be
gauged in terms of an entropy value associated to their
evolution. Smooth approximations of entropy highlight regions where
classification is most uncertain. Promising results are obtained when
methods proposed are applied in the Optimal Sampling framework.},
  LINK = {http://mpa.itc.it/papers/caprile2002highlighting.pdf}
}

@BOOK{netelermitasova2002,
  AUTHOR = {M. Neteler and H. Mitasova},
  TITLE = {Open {S}ource {GIS}: {A} {GRASS} {GIS} {A}pproach},
  YEAR = {2002},
  PAGES = {464},
  PUBLISHER = {Kluwer Academic Publishers},
  ADDRESS = {Boston, Dordrecht, London},
  NOTE = {ISBN: 1-4020-7088-8},
  KEYWORDS = {GIS, Geographic Information Systems, Open Source, Software},
  SERIES = {The Kluwer international series in Engineering and Computer
          Science (SECS): Volume 689},
  LINK = {http://mpa.itc.it/grassbook/index.html},
  ABSTRACT = {Open Source Software is one of the most striking innovations in
    software development in the 1990s. It has been stimulated by the
    success of LINUX and the Internet which facilitated global
    communication as well as data and software exchange. The
    Geographical Information System GRASS (Geographical
    Resources Analysis Support System) is the largest Free Software
    GIS Project and by the size of the code it belongs to the top ten list
    of all Open Source Projects worldwide. 
    Open Source GIS: A GRASS GIS Approach was written for
    experienced GIS users, who want to learn GRASS, as well as for the
    Open Source software users who are GIS newcomers. 
    Following the Open Source model of GRASS, the book includes
    links to sites where the GRASS system and on-line reference
    manuals can be downloaded and additional applications can be
    viewed. The project's web site can be reached at http://grass.itc.it
    and a number of mirror sites worldwide. 
    Open Source GIS: A GRASS GIS Approach, provides basic
    information about the use of GRASS from setting up the spatial
    database, through working with raster, vector and site data, to image
    processing and hands-on applications. This book also contains a
    brief introduction to programming within GRASS encouraging the
    new GRASS development. The power of computing within Open
    Source environment is illustrated by examples of the GRASS usage
    with other Open Source software tools, such as GSTAT, R
    statistical language, and linking GRASS to MapServer. 
    Open Source GIS: A GRASS GIS Approach is designed to meet
    the needs of a professional audience composed of researchers and
    practitioners in industry and graduate level students in Computer
    Science and Geosciences. 
    http://mpa.itc.it/grassbook/open_source_gis2002.pdf}
}