The research platform for building medical diagnostic services

This paper describes research and development of a software platform for processing medical diagnostic data. This work is carried out by the IT-park of PetrSU in collaboration with the Faculty of Medicine. The aim of the Platform development is to present universal software tools for research done on the basis of the initial information on the diseases, and the mathematical methods of data processing. The paper describes the software platform general architecture, as well as the methods of diagnostic rules creation using the iteration model and the poly-procedural approach. The offered methods have sufficient generality and can be applied in research of a wide range of diseases

Focal Spot, Winter 2007/2008

https://digitalcommons.wustl.edu/focal_spot_archives/1107/thumbnail.jp

Business Models for e-Health: Evidence from Ten Case Studies

An increasingly aging population and spiraling healthcare costs have made the search for financially viable healthcare models an imperative of this century. The careful and creative application of information technology can play a significant role in meeting that challenge. Valuable lessons can be learned from an analysis of ten innovative telemedicine and e-health initiatives. Having proven their effectiveness in addressing a variety of medical needs, they have progressed beyond small-scale implementations to become an established part of healthcare delivery systems around the world

J-PET Framework: Software platform for PET tomography data reconstruction and analysis

J-PET Framework is an open-source software platform for data analysis, written in C++ and based on the ROOT package. It provides a common environment for implementation of reconstruction, calibration and filtering procedures, as well as for user-level analyses of Positron Emission Tomography data. The library contains a set of building blocks that can be combined by users with even little programming experience, into chains of processing tasks through a convenient, simple and well-documented API. The generic input-output interface allows processing the data from various sources: low-level data from the tomography acquisition system or from diagnostic setups such as digital oscilloscopes, as well as high-level tomography structures e.g. sinograms or a list of lines-of-response. Moreover, the environment can be interfaced with Monte Carlo simulation packages such as GEANT and GATE, which are commonly used in the medical scientific community.Comment: 14 pages, 5 figure

Focal Spot, Winter 2006/2007

https://digitalcommons.wustl.edu/focal_spot_archives/1104/thumbnail.jp