Synergy between medical informatics and bioinformatics: facilitating genomic medicine for future health care

Medical Informatics (MI) and Bioinformatics (BI) are two interdisciplinary areas located at the intersection between computer science and medicine and biology, respectively. Historically, they have been separated and only occasionally have researchers of both disciplines collaborated. The completion of the Human Genome Project has brought about in this post genomic era the need for a synergy of these two disciplines to further advance in the study of diseases by correlating essential genotypic information with expressed phenotypic information. Biomedical Informatics (BMI) is the emerging technology that aims to put these two worlds together in the new rising genomic medicine. In this regard, institutions such as the European Commission have recently launched several initiatives to support a new combined research agenda, based on the potential for synergism of both disciplines. In this paper we review the results the BIOINFOMED study one of these projects funded by the E

Reviewing the integration of patient data: how systems are evolving in practice to meet patient needs

<p>Abstract</p> <p>Background</p> <p>The integration of Information Systems (IS) is essential to support shared care and to provide consistent care to individuals – patient-centred care. This paper identifies, appraises and summarises studies examining different approaches to integrate patient data from heterogeneous IS.</p> <p>Methods</p> <p>The literature was systematically reviewed between 1995–2005 to identify articles mentioning patient records, computers and data integration or sharing.</p> <p>Results</p> <p>Of 3124 articles, 84 were included describing 56 distinct projects. Most of the projects were on a regional scale. Integration was most commonly accomplished by messaging with pre-defined templates and middleware solutions. HL7 was the most widely used messaging standard. Direct database access and web services were the most common communication methods. The user interface for most systems was a Web browser. Regarding the type of medical data shared, 77% of projects integrated diagnosis and problems, 67% medical images and 65% lab results. More recently significantly more IS are extending to primary care and integrating referral letters.</p> <p>Conclusion</p> <p>It is clear that Information Systems are evolving to meet people's needs by implementing regional networks, allowing patient access and integration of ever more items of patient data. Many distinct technological solutions coexist to integrate patient data, using differing standards and data architectures which may difficult further interoperability.</p

C: A System for the Indexing, Storage, and Retrieval of Medical Images by Content

Image indexing, storage, and retrieval based on pictorial content is a feature of image database systems which is becoming of increasing importance in many application domains. Medical image database systems, which support the retrieval of images generated by different modalities based on their pictorial content, will provide added value to future generation Picture Archiving and Communication Systems (PACS), and can be used as a diagnostic decision support tool and as a tool for medical research and training. This paper presents the architecture and features of I 2 C, a system for the indexing, storage, and retrieval of medical images by content. A unique design feature of this architecture is that it also serves as a platform for the implementation and performance evaluation of image description methods and retrieval strategies. I 2 C is a modular and extensible system, which has been developed based on object-oriented principles. It consists of a set of cooperating modules which..

I&amp;sup2;C: A System for the Indexing, Storage, and Retrieval of Medical Images by Content

Image indexing, storage, and retrieval based on pictorial content is a feature of image database systems which is becoming of increasing importance in many application domains. Medical image database systems, which support the retrieval of images generated by different modalities based on their pictorial content, will provide added value to future generation Picture Archiving and Communication Systems (PACS), and can be used as a diagnostic decision support tool and as a tool for medical research and training. This paper presents the architecture and features of I 2 C, a system for the indexing, storage, and retrieval of medical images by content. A unique design feature of this architecture is that it also serves as a platform for the implementation and performance evaluation of image description methods and retrieval strategies. I 2 C is a modular and extensible system, which has been developed based on object-oriented principles. It consists of a set of cooperating modules which..

DIPE: A Distributed Environment for Medical Image Processing

. DIPE is a distributed environment that provides image processing services over integrated teleradiology services networks. DIPE integrates existing and new image processing software and employs sophisticated execution scheduling mechanisms for the efficient management of computational resources within a distributed environment. It can also be extended to provide various addedvalue services, such as management and retrieval of image processing software modules, as well as advanced charging procedures based on quality of service. DIPE can be viewed as the natural evolution of the legacy field of medical image processing towards a service over the emergent health care telematics networks. 1. Introduction In recent years, advances in information technology and telecommunications have acted as catalysts for significant developments in the sector of health care. These technological advances have had a particularly strong impact in the field of medical imaging, where film radiographic tech..

The Architecture of a System for the Indexing of Images by Content

This paper presents the architecture of an image database system which provides a platform for the accommodation of various algorithms for interactive and automatic indexing, storage, and retrieval of medical images by content. The system maintains a dynamic hierarchy of image classes. The class hierarchy is used to narrowdown the search to images of the same modality, anatomical characteristics, etc. Each image is classi#ed into an image class based on information supplied by the user or obtained from the image itself. An important feature of the system is its ability to support multiple image indexing by content methods, in the form of description types. During system installation, one or more description types are selected for each image class based on the inherentcharacteristics of the class. Then, for each description type, a content description of each image in the class is generated and inserted in the description database. In the case of a query, the system generates one or more descriptions of the query image, automatically or interactively, and searches the logical database for similar descriptions. The images whose descriptions match those of the query image are retrieved for browsing by the user. This system may also be used as a platform for evaluating image content description methods, since new methods can be added to it easil