Carpal Tunnel Syndrome automatic classification: electromyography vs. ultrasound imaging View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2015-04

AUTHORS

Maurizio Maravalle, Federica Ricca, Bruno Simeone, Vincenzo Spinelli

ABSTRACT

We study automatic classification for the diagnosis of the Carpal Tunnel Syndrome (CTS), a disease frequently observed in occupational medicine. We apply different classification techniques to two real-life medical data sets related to a group of patients reporting the typical symptoms of this syndrome. We are particularly interested in the performance of “Box-Clustering” (BC), a method that is able to favor readability and interpretation of the results by medical doctors, thanks to its “box-type” output which naturally configures as a medical report. Preliminary results of a basic implementation of BC applied to different data sets already exist in the literature, and here we add more. In particular, in this paper, we apply a recently developed (and specialized) implementation of BC, and we test it for the first time on real-life medical data related to the CTS. Our purpose is to evaluate the performance of BC for automatic diagnosis, as well as, gain in explanation capability and interpretability. This is, in fact, a crucial aspect in medical applications that generally represents a limit for other well-known and powerful classification techniques. More... »

PAGES

100-123

References to SciGraph publications

  • 2003-03. Coronary Risk Prediction by Logical Analysis of Data in ANNALS OF OPERATIONS RESEARCH
  • 2009-10-15. Classification Techniques and Error Control in Logic Mining in DATA MINING
  • 2010-03. Morphological Analysis of the Carpal Tunnel in HAND
  • 2002-05. Different case definitions to describe the prevalence of occupational carpal tunnel syndrome in meat industry workers in INTERNATIONAL ARCHIVES OF OCCUPATIONAL AND ENVIRONMENTAL HEALTH
  • 1988-12. Cause-effect relationships and partially defined Boolean functions in ANNALS OF OPERATIONS RESEARCH
  • 2006. Learning Logic Formulas and Related Error Distributions in DATA MINING AND KNOWLEDGE DISCOVERY APPROACHES BASED ON RULE INDUCTION TECHNIQUES
  • 2006-11. Logical analysis of data—An overview: From combinatorial optimization to medical applications in ANNALS OF OPERATIONS RESEARCH
  • 1997-11. Carpal tunnel syndrome: A review in CLINICAL RHEUMATOLOGY
  • 2006-08. Breast cancer prognosis by combinatorial analysis of gene expression data in BREAST CANCER RESEARCH
  • 2002-12. The Maximum Box Problem and its Application to Data Analysis in COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
  • 2006. Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques in NONE
  • 1997-10. Logical analysis of numerical data in MATHEMATICAL PROGRAMMING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11750-014-0325-0

    DOI

    http://dx.doi.org/10.1007/s11750-014-0325-0

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1045591093


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Artificial Intelligence and Image Processing", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "University of L'Aquila", 
              "id": "https://www.grid.ac/institutes/grid.158820.6", 
              "name": [
                "Dip. di Ingegneria e Scienze dell\u2019Informazione e Matematica, Universit\u00e0 degli Studi dell\u2019Aquila, L\u2019Aquila, Italy"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Maravalle", 
            "givenName": "Maurizio", 
            "id": "sg:person.01171206147.24", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01171206147.24"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Sapienza University of Rome", 
              "id": "https://www.grid.ac/institutes/grid.7841.a", 
              "name": [
                "Dip. di Scienze Statistiche, Sapienza Universit\u00e0 di Roma, Rome, Italy"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ricca", 
            "givenName": "Federica", 
            "id": "sg:person.016420256135.86", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016420256135.86"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Sapienza University of Rome", 
              "id": "https://www.grid.ac/institutes/grid.7841.a", 
              "name": [
                "Dip. di Scienze Statistiche, Sapienza Universit\u00e0 di Roma, Rome, Italy"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Simeone", 
            "givenName": "Bruno", 
            "id": "sg:person.012600006066.78", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012600006066.78"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "National Institute of Statistics", 
              "id": "https://www.grid.ac/institutes/grid.425381.9", 
              "name": [
                "Istituto Nazionale di Statistica (Istat), Rome, Italy"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Spinelli", 
            "givenName": "Vincenzo", 
            "id": "sg:person.012112744414.39", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012112744414.39"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1023/a:1022970120229", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003490585", 
              "https://doi.org/10.1023/a:1022970120229"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4419-1280-0_5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004841740", 
              "https://doi.org/10.1007/978-1-4419-1280-0_5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4419-1280-0_5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004841740", 
              "https://doi.org/10.1007/978-1-4419-1280-0_5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00420-001-0304-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008745085", 
              "https://doi.org/10.1007/s00420-001-0304-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02247800", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008989166", 
              "https://doi.org/10.1007/bf02247800"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02247800", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008989166", 
              "https://doi.org/10.1007/bf02247800"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02283750", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009714991", 
              "https://doi.org/10.1007/bf02283750"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02283750", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009714991", 
              "https://doi.org/10.1007/bf02283750"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10479-006-0075-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009767861", 
              "https://doi.org/10.1007/s10479-006-0075-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10479-006-0075-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009767861", 
              "https://doi.org/10.1007/s10479-006-0075-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11552-009-9220-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010109107", 
              "https://doi.org/10.1007/s11552-009-9220-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11552-009-9220-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010109107", 
              "https://doi.org/10.1007/s11552-009-9220-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0033-8389(05)70132-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015783169"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0033-8389(05)70132-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015783169"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0363-5023(87)80054-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015923421"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ejor.2010.03.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017121646"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.dam.2003.08.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019342117"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.dam.2004.05.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019668322"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0166-218x(02)00205-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028416219"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1656274.1656278", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028526411"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02614316", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032847525", 
              "https://doi.org/10.1007/bf02614316"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02614316", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032847525", 
              "https://doi.org/10.1007/bf02614316"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/mus.10227", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035208973"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/bcr1512", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037342198", 
              "https://doi.org/10.1186/bcr1512"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0304-3975(98)00337-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037424054"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/0-387-34296-6_5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038738290", 
              "https://doi.org/10.1007/0-387-34296-6_5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.dam.2005.02.035", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039343850"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/a:1020546910706", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045163626", 
              "https://doi.org/10.1023/a:1020546910706"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/0-387-34296-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053522031", 
              "https://doi.org/10.1007/0-387-34296-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/0-387-34296-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053522031", 
              "https://doi.org/10.1007/0-387-34296-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/69.842268", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061213820"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/69.842268", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061213820"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tkde.2005.50", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061661459"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1162/15268740052050988", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1063350193"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1214/09-ss054", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064391087"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1287/ijoc.1090.0317", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064706732"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1287/ijoc.13.1.1.9747", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064707029"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1082821043", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1090/dimacs/055", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1097022693"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2015-04", 
        "datePublishedReg": "2015-04-01", 
        "description": "We study automatic classification for the diagnosis of the Carpal Tunnel Syndrome (CTS), a disease frequently observed in occupational medicine. We apply different classification techniques to two real-life medical data sets related to a group of patients reporting the typical symptoms of this syndrome. We are particularly interested in the performance of \u201cBox-Clustering\u201d (BC), a method that is able to favor readability and interpretation of the results by medical doctors, thanks to its \u201cbox-type\u201d output which naturally configures as a medical report. Preliminary results of a basic implementation of BC applied to different data sets already exist in the literature, and here we add more. In particular, in this paper, we apply a recently developed (and specialized) implementation of BC, and we test it for the first time on real-life medical data related to the CTS. Our purpose is to evaluate the performance of BC for automatic diagnosis, as well as, gain in explanation capability and interpretability. This is, in fact, a crucial aspect in medical applications that generally represents a limit for other well-known and powerful classification techniques.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s11750-014-0325-0", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1136537", 
            "issn": [
              "1134-5764", 
              "1863-8279"
            ], 
            "name": "TOP", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "23"
          }
        ], 
        "name": "Carpal Tunnel Syndrome automatic classification: electromyography vs. ultrasound imaging", 
        "pagination": "100-123", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "d92bbce0216f89807c66f68695bcaaf3455dc00db699cc85e9f7d75e11564777"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s11750-014-0325-0"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1045591093"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s11750-014-0325-0", 
          "https://app.dimensions.ai/details/publication/pub.1045591093"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T22:35", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8690_00000524.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007%2Fs11750-014-0325-0"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11750-014-0325-0'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11750-014-0325-0'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11750-014-0325-0'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11750-014-0325-0'


     

    This table displays all metadata directly associated to this object as RDF triples.

    189 TRIPLES      21 PREDICATES      57 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s11750-014-0325-0 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author N6a22309e438b4ecca657b43ea27aa9b5
    4 schema:citation sg:pub.10.1007/0-387-34296-6
    5 sg:pub.10.1007/0-387-34296-6_5
    6 sg:pub.10.1007/978-1-4419-1280-0_5
    7 sg:pub.10.1007/bf02247800
    8 sg:pub.10.1007/bf02283750
    9 sg:pub.10.1007/bf02614316
    10 sg:pub.10.1007/s00420-001-0304-2
    11 sg:pub.10.1007/s10479-006-0075-y
    12 sg:pub.10.1007/s11552-009-9220-9
    13 sg:pub.10.1023/a:1020546910706
    14 sg:pub.10.1023/a:1022970120229
    15 sg:pub.10.1186/bcr1512
    16 https://app.dimensions.ai/details/publication/pub.1082821043
    17 https://doi.org/10.1002/mus.10227
    18 https://doi.org/10.1016/j.dam.2003.08.013
    19 https://doi.org/10.1016/j.dam.2004.05.002
    20 https://doi.org/10.1016/j.dam.2005.02.035
    21 https://doi.org/10.1016/j.ejor.2010.03.020
    22 https://doi.org/10.1016/s0033-8389(05)70132-9
    23 https://doi.org/10.1016/s0166-218x(02)00205-6
    24 https://doi.org/10.1016/s0304-3975(98)00337-5
    25 https://doi.org/10.1016/s0363-5023(87)80054-0
    26 https://doi.org/10.1090/dimacs/055
    27 https://doi.org/10.1109/69.842268
    28 https://doi.org/10.1109/tkde.2005.50
    29 https://doi.org/10.1145/1656274.1656278
    30 https://doi.org/10.1162/15268740052050988
    31 https://doi.org/10.1214/09-ss054
    32 https://doi.org/10.1287/ijoc.1090.0317
    33 https://doi.org/10.1287/ijoc.13.1.1.9747
    34 schema:datePublished 2015-04
    35 schema:datePublishedReg 2015-04-01
    36 schema:description We study automatic classification for the diagnosis of the Carpal Tunnel Syndrome (CTS), a disease frequently observed in occupational medicine. We apply different classification techniques to two real-life medical data sets related to a group of patients reporting the typical symptoms of this syndrome. We are particularly interested in the performance of “Box-Clustering” (BC), a method that is able to favor readability and interpretation of the results by medical doctors, thanks to its “box-type” output which naturally configures as a medical report. Preliminary results of a basic implementation of BC applied to different data sets already exist in the literature, and here we add more. In particular, in this paper, we apply a recently developed (and specialized) implementation of BC, and we test it for the first time on real-life medical data related to the CTS. Our purpose is to evaluate the performance of BC for automatic diagnosis, as well as, gain in explanation capability and interpretability. This is, in fact, a crucial aspect in medical applications that generally represents a limit for other well-known and powerful classification techniques.
    37 schema:genre research_article
    38 schema:inLanguage en
    39 schema:isAccessibleForFree false
    40 schema:isPartOf Nbd4c7179227f4eeab6bcd14271947b7b
    41 Nbf7407c93b8b447d8555d3d372dcee0f
    42 sg:journal.1136537
    43 schema:name Carpal Tunnel Syndrome automatic classification: electromyography vs. ultrasound imaging
    44 schema:pagination 100-123
    45 schema:productId N2e56bc89d71143e992f8e3f14d7a9142
    46 N540daba8e4c246edb531c94d3a2cb855
    47 Nafaaa1472a3a475bbc17ec596dc2d2e7
    48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045591093
    49 https://doi.org/10.1007/s11750-014-0325-0
    50 schema:sdDatePublished 2019-04-10T22:35
    51 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    52 schema:sdPublisher Ne1dc6731553449d694d0585750e77b9d
    53 schema:url http://link.springer.com/10.1007%2Fs11750-014-0325-0
    54 sgo:license sg:explorer/license/
    55 sgo:sdDataset articles
    56 rdf:type schema:ScholarlyArticle
    57 N2e56bc89d71143e992f8e3f14d7a9142 schema:name readcube_id
    58 schema:value d92bbce0216f89807c66f68695bcaaf3455dc00db699cc85e9f7d75e11564777
    59 rdf:type schema:PropertyValue
    60 N540daba8e4c246edb531c94d3a2cb855 schema:name dimensions_id
    61 schema:value pub.1045591093
    62 rdf:type schema:PropertyValue
    63 N6a22309e438b4ecca657b43ea27aa9b5 rdf:first sg:person.01171206147.24
    64 rdf:rest Nd7033fa93c5f4d7489db8647beebb572
    65 Nafaaa1472a3a475bbc17ec596dc2d2e7 schema:name doi
    66 schema:value 10.1007/s11750-014-0325-0
    67 rdf:type schema:PropertyValue
    68 Nb638f76d6aca4f9c9907da50d46e2a15 rdf:first sg:person.012112744414.39
    69 rdf:rest rdf:nil
    70 Nbd4c7179227f4eeab6bcd14271947b7b schema:issueNumber 1
    71 rdf:type schema:PublicationIssue
    72 Nbf7407c93b8b447d8555d3d372dcee0f schema:volumeNumber 23
    73 rdf:type schema:PublicationVolume
    74 Nd1f8ba3f88454c2b8823a4d1387df905 rdf:first sg:person.012600006066.78
    75 rdf:rest Nb638f76d6aca4f9c9907da50d46e2a15
    76 Nd7033fa93c5f4d7489db8647beebb572 rdf:first sg:person.016420256135.86
    77 rdf:rest Nd1f8ba3f88454c2b8823a4d1387df905
    78 Ne1dc6731553449d694d0585750e77b9d schema:name Springer Nature - SN SciGraph project
    79 rdf:type schema:Organization
    80 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    81 schema:name Information and Computing Sciences
    82 rdf:type schema:DefinedTerm
    83 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    84 schema:name Artificial Intelligence and Image Processing
    85 rdf:type schema:DefinedTerm
    86 sg:journal.1136537 schema:issn 1134-5764
    87 1863-8279
    88 schema:name TOP
    89 rdf:type schema:Periodical
    90 sg:person.01171206147.24 schema:affiliation https://www.grid.ac/institutes/grid.158820.6
    91 schema:familyName Maravalle
    92 schema:givenName Maurizio
    93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01171206147.24
    94 rdf:type schema:Person
    95 sg:person.012112744414.39 schema:affiliation https://www.grid.ac/institutes/grid.425381.9
    96 schema:familyName Spinelli
    97 schema:givenName Vincenzo
    98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012112744414.39
    99 rdf:type schema:Person
    100 sg:person.012600006066.78 schema:affiliation https://www.grid.ac/institutes/grid.7841.a
    101 schema:familyName Simeone
    102 schema:givenName Bruno
    103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012600006066.78
    104 rdf:type schema:Person
    105 sg:person.016420256135.86 schema:affiliation https://www.grid.ac/institutes/grid.7841.a
    106 schema:familyName Ricca
    107 schema:givenName Federica
    108 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016420256135.86
    109 rdf:type schema:Person
    110 sg:pub.10.1007/0-387-34296-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053522031
    111 https://doi.org/10.1007/0-387-34296-6
    112 rdf:type schema:CreativeWork
    113 sg:pub.10.1007/0-387-34296-6_5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038738290
    114 https://doi.org/10.1007/0-387-34296-6_5
    115 rdf:type schema:CreativeWork
    116 sg:pub.10.1007/978-1-4419-1280-0_5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004841740
    117 https://doi.org/10.1007/978-1-4419-1280-0_5
    118 rdf:type schema:CreativeWork
    119 sg:pub.10.1007/bf02247800 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008989166
    120 https://doi.org/10.1007/bf02247800
    121 rdf:type schema:CreativeWork
    122 sg:pub.10.1007/bf02283750 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009714991
    123 https://doi.org/10.1007/bf02283750
    124 rdf:type schema:CreativeWork
    125 sg:pub.10.1007/bf02614316 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032847525
    126 https://doi.org/10.1007/bf02614316
    127 rdf:type schema:CreativeWork
    128 sg:pub.10.1007/s00420-001-0304-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008745085
    129 https://doi.org/10.1007/s00420-001-0304-2
    130 rdf:type schema:CreativeWork
    131 sg:pub.10.1007/s10479-006-0075-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1009767861
    132 https://doi.org/10.1007/s10479-006-0075-y
    133 rdf:type schema:CreativeWork
    134 sg:pub.10.1007/s11552-009-9220-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010109107
    135 https://doi.org/10.1007/s11552-009-9220-9
    136 rdf:type schema:CreativeWork
    137 sg:pub.10.1023/a:1020546910706 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045163626
    138 https://doi.org/10.1023/a:1020546910706
    139 rdf:type schema:CreativeWork
    140 sg:pub.10.1023/a:1022970120229 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003490585
    141 https://doi.org/10.1023/a:1022970120229
    142 rdf:type schema:CreativeWork
    143 sg:pub.10.1186/bcr1512 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037342198
    144 https://doi.org/10.1186/bcr1512
    145 rdf:type schema:CreativeWork
    146 https://app.dimensions.ai/details/publication/pub.1082821043 schema:CreativeWork
    147 https://doi.org/10.1002/mus.10227 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035208973
    148 rdf:type schema:CreativeWork
    149 https://doi.org/10.1016/j.dam.2003.08.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019342117
    150 rdf:type schema:CreativeWork
    151 https://doi.org/10.1016/j.dam.2004.05.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019668322
    152 rdf:type schema:CreativeWork
    153 https://doi.org/10.1016/j.dam.2005.02.035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039343850
    154 rdf:type schema:CreativeWork
    155 https://doi.org/10.1016/j.ejor.2010.03.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017121646
    156 rdf:type schema:CreativeWork
    157 https://doi.org/10.1016/s0033-8389(05)70132-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015783169
    158 rdf:type schema:CreativeWork
    159 https://doi.org/10.1016/s0166-218x(02)00205-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028416219
    160 rdf:type schema:CreativeWork
    161 https://doi.org/10.1016/s0304-3975(98)00337-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037424054
    162 rdf:type schema:CreativeWork
    163 https://doi.org/10.1016/s0363-5023(87)80054-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015923421
    164 rdf:type schema:CreativeWork
    165 https://doi.org/10.1090/dimacs/055 schema:sameAs https://app.dimensions.ai/details/publication/pub.1097022693
    166 rdf:type schema:CreativeWork
    167 https://doi.org/10.1109/69.842268 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061213820
    168 rdf:type schema:CreativeWork
    169 https://doi.org/10.1109/tkde.2005.50 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061661459
    170 rdf:type schema:CreativeWork
    171 https://doi.org/10.1145/1656274.1656278 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028526411
    172 rdf:type schema:CreativeWork
    173 https://doi.org/10.1162/15268740052050988 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063350193
    174 rdf:type schema:CreativeWork
    175 https://doi.org/10.1214/09-ss054 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064391087
    176 rdf:type schema:CreativeWork
    177 https://doi.org/10.1287/ijoc.1090.0317 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064706732
    178 rdf:type schema:CreativeWork
    179 https://doi.org/10.1287/ijoc.13.1.1.9747 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064707029
    180 rdf:type schema:CreativeWork
    181 https://www.grid.ac/institutes/grid.158820.6 schema:alternateName University of L'Aquila
    182 schema:name Dip. di Ingegneria e Scienze dell’Informazione e Matematica, Università degli Studi dell’Aquila, L’Aquila, Italy
    183 rdf:type schema:Organization
    184 https://www.grid.ac/institutes/grid.425381.9 schema:alternateName National Institute of Statistics
    185 schema:name Istituto Nazionale di Statistica (Istat), Rome, Italy
    186 rdf:type schema:Organization
    187 https://www.grid.ac/institutes/grid.7841.a schema:alternateName Sapienza University of Rome
    188 schema:name Dip. di Scienze Statistiche, Sapienza Università di Roma, Rome, Italy
    189 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...