  The next generation of High Energy Physics (HEP) experiments requires a GRID
approach to a distributed computing system and the associated data management:
the key concept is the Virtual Organisation (VO), a group of distributed users
with a common goal and the will to share their resources. A similar approach is
being applied to a group of Hospitals which joined the GPCALMA project (Grid
Platform for Computer Assisted Library for MAmmography), which will allow
common screening programs for early diagnosis of breast and, in the future,
lung cancer. HEP techniques come into play in writing the application code,
which makes use of neural networks for the image analysis and proved to be
useful in improving the radiologists' performances in the diagnosis. GRID
technologies allow remote image analysis and interactive online diagnosis, with
a potential for a relevant reduction of the delays presently associated to
screening programs. A prototype of the system, based on AliEn GRID Services, is
already available, with a central Server running common services and several
clients connecting to it. Mammograms can be acquired in any location; the
related information required to select and access them at any time is stored in
a common service called Data Catalogue, which can be queried by any client. The
result of a query can be used as input for analysis algorithms, which are
executed on nodes that are in general remote to the user (but always local to
the input images) thanks to the PROOF facility. The selected approach avoids
data transfers for all the images with a negative diagnosis (about 95% of the
sample) and allows an almost real time diagnosis for the 5% of images with high
cancer probability.
