PubMed · 10163136
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B Rubenzer. Coding for medical imaging.. https://pubmed.ncbi.nlm.nih.gov/10163136/
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A fundamental requirement for achieving continuity of care is the seamless sharing of multimedia clinical information. Different technological approaches can be adopted for enabling the communication and sharing of health record segments. In the context of the emerging global information society, the creation of and access to the integrated electronic health record (I-EHR) of a citizen has been assigned high priority in many countries. This requirement is complementary to an overall requirement for the creation of a health information infrastructure (HII) to support the provision of a variety of health telematics and e-health services. In developing a regional or national HII, the components or building blocks that make up the overall information system ought to be defined and an appropriate component architecture specified. This paper discusses current international priorities and trends in developing the HII. It presents technological challenges and alternative approaches towards the creation of an I-EHR, being the aggregation of health data created during all interactions of an individual with the healthcare system. It also presents results from an ongoing Research and Development (R&D) effort towards the implementation of the HII in HYGEIAnet, the regional health information network of Crete, Greece, using a component-based software engineering approach. Critical design decisions and related trade-offs, involved in the process of component specification and development, are also discussed and the current state of development of an I-EHR service is presented. Finally, Human Computer Interaction (HCI) and security issues, which are important for the deployment and use of any I-EHR service, are considered.
Literature mining is the process of extracting and combining facts from scientific publications. In recent years, many computer programs have been designed to extract various molecular biology findings from Medline abstracts or full-text articles. The present article describes the range of text mining techniques that have been applied to scientific documents. It divides 'automated reading' into four general subtasks: text categorization, named entity tagging, fact extraction, and collection-wide analysis. Literature mining offers powerful methods to support knowledge discovery and the construction of topic maps and ontologies. An overview is given of recent developments in medical language processing. Special attention is given to the domain particularities of molecular biology, and the emerging synergy between literature mining and molecular databases accessible through Internet.
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