{
  "annotation_id": "33754c20-1cfa-41d9-b8c7-41da6a81f783",
  "date_created": "2026-03-02T18:00:53.424000Z",
  "date_modified": "2026-03-02T18:00:53.424000Z",
  "file_hash": "c44c212596ce9ed692fb79a9954aa7bb1cf99ff8dee847b5638e73573dc4e003",
  "private": false,
  "record": {
    "abstract": "The next generation of High Energy Physics (HEP) experiments requires a GRID\napproach to a distributed computing system and the associated data management:\nthe key concept is the Virtual Organisation (VO), a group of distributed users\nwith a common goal and the will to share their resources. A similar approach is\nbeing applied to a group of Hospitals which joined the GPCALMA project (Grid\nPlatform for Computer Assisted Library for MAmmography), which will allow\ncommon screening programs for early diagnosis of breast and, in the future,\nlung cancer. HEP techniques come into play in writing the application code,\nwhich makes use of neural networks for the image analysis and proved to be\nuseful in improving the radiologists\u0027 performances in the diagnosis. GRID\ntechnologies allow remote image analysis and interactive online diagnosis, with\na potential for a relevant reduction of the delays presently associated to\nscreening programs. A prototype of the system, based on AliEn GRID Services, is\nalready available, with a central Server running common services and several\nclients connecting to it. Mammograms can be acquired in any location; the\nrelated information required to select and access them at any time is stored in\na common service called Data Catalogue, which can be queried by any client. The\nresult of a query can be used as input for analysis algorithms, which are\nexecuted on nodes that are in general remote to the user (but always local to\nthe input images) thanks to the PROOF facility. The selected approach avoids\ndata transfers for all the images with a negative diagnosis (about 95% of the\nsample) and allows an almost real time diagnosis for the 5% of images with high\ncancer probability.",
    "arxiv_id": "physics/0410085",
    "authors": [
      "S. Bagnasco",
      "U. Bottigli",
      "P. Cerello",
      "S. C. Cheran",
      "P. Delogu",
      "M. E. Fantacci",
      "F. Fauci",
      "G. Forni",
      "A. Lauria",
      "E. Lopez Torres",
      "R. Magro",
      "G. L. Masala",
      "P. Oliva",
      "R. Palmiero",
      "L. Ramello",
      "G. Raso",
      "A. Retico",
      "M. Sitta",
      "S. Stumbo",
      "S. Tangaro",
      "E. Zanon"
    ],
    "categories": [
      "physics.med-ph"
    ],
    "journal_ref": "Methods Inf. Med. 44(2) 244-8 (2005)",
    "title": "GPCALMA: a Grid-based tool for Mammographic Screening",
    "url": "https://arxiv.org/abs/physics/0410085"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "0e023eba-ca1c-4a68-b95e-7922cbd91ffd",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}