International journal of bio-medical computing最新文献

The main goal of this paper is to show the usefulness of the logic-combinatory approach in pattern recognition theory for developing auxiliary criteria for differential medical diagnosis, based on the methodology presented by Heathfield et al. (J Biomed Eng 13 (1991) 51–57). Firstly, we propose a change in the characterization base, from disease characterization to patient characterization then, we suggest a k-valued treatment for variables which allows us to assign them values in a wider range in order to represent different degrees in symptom manifestations. Secondly, the methodology proposed is based on Testor Theory. This theory allows us to obtain the minimum combination of features (symptoms) and the set of features combination equally discriminant (typical testors) among the diseases considered. Then, applying some classification algorithm that uses typical testors, physicians will have more making differential flexibility diagnosis.

The traditional approach to the development of knowledge-based systems (KBS) has been rule-based, where heuristic knowledge is encoded in a set of production rules. A rule-based reasoning (RBR) system needs a well constructed domain theory as its reasoning basis, and it does not make substantial use of the knowledge embedded in previous cases. An RBR system performs relatively well in a knowledge-rich application environment. Although its capability may be limited when previous experiences are not a good representation of the whole population, a case-based reasoning (CBR) system is capable of using past experiences as problem solving tools, therefore, it is appropriate for an experience-rich domain. In recent years, both RBR and CBR have emerged as important and complementary reasoning methodologies in artificial intelligence. For problem solving in AIDS intervention and prevention, it is useful to integrate RBR and CBR. In this paper, a hybrid KBS which integrates a deductive RBR system and an inductive CRB system is proposed to assess AIDS-risky behaviors.

During the testing of the Read Clinical Codes in general practice medical records in Australia, it became apparent that the pharmaceutical section of the codes was not applicable in a country with different brand names, pack sizes and forms. For pharmacoepidemiological studies, structured classification of both morbidity and pharmaceuticals is required for meaningful analysis. The search for a suitable pharmaceutical classification proved fruitless. While the Australian Government has recently adopted the Anatomical Therapeutic Chemical (ATC) Classification as the national standard, this only classifies drugs to the generic level. None of the extended coding systems used in hospital pharmacies, by community pharmacists, or by Government are hierarchically structured. The extension code we have developed, is an analytical algorithm comprising independent fields for: dosage; strength; manufacturer and brand; and pack size. The codes within each field are also structured in a hierarchical manner. The result is an extension code of 21 digits, each digit or group of digits having a meaning. The structure of this classification will allow analysis of any aspect of the drug prescribed. This system is designed for computerised entry of text and transparent coding of the data — not for manual coding on paper nor manual code entry to the computer.

In the recent years, multimedia has exhibited a tremendous presence in the personal computer market and it has exerted an influence in our homes and teaching institutions as well. To define it very simply, a multimedia PC is a personal computer capable of producing images and sound of reasonable quality by means of software toggles. This paper presents an Asymetrix Multimedia Toolbook application entitled Multimedia Clinical Examination (MCE) which harnesses the ability of affordable computers to create and display a variety of audiovisual media to supplement ‘bed-side teaching’ of elementary clinical methods which includes history taking and physical examination. MCE comprises a history taking module which helps in keeping track of the possible differential diagnoses and a physical examination module which shows digital videos of appropriate examination steps. The application runs on the Microsoft Windows platform.

‘Black box’ expert systems (ES) are mistrusted by clinicians. Errors generated by medical ES are also a significant cause for concern. We report new ES properties — prudence and credentials — that improve error management and underpin a new approach for improving the credibility of ES for clinical users. Prudent ES modify their output according to past experience. For a knowledge base built from 1610 cases, feature exception prudence (FEP) detected all interpretation errors (100% sensitivity for error detection). Although the false positive rate for FEP was high (47%), the 100%) sensitivity meant that the 53% of cases that did not produce flags could be exempted from human validation. As more cases are processed, fewer cases should need human validation. Feature recognition prudence (FRP), a property of ripple down rules (RDR), proposed the correct alternative conclusion in 14% of incorrectly interpreted cases. Human expert validation of the flagged cases enabled context-sensitive credentials (accuracy, incidence and specificity of a given conclusion) to accumulate. Credentials should enable the user to judge the credibility of the ES output. An error management strategy based on credentialled, prudent ES should reduce the impact of error in the clinical environment. The empowerment of clinicians to critically evaluate ES credibility may facilitate greater confidence in, and acceptance of, ES by clinicians.

Small units with specialised functions often have difficulty in developing information systems because of their unique and dynamic requirements, the smallness of their applications relative to the large inter-organisational networks, and the sheer numbers of such units, especially in government. Personal experience with the difficulty of establishing a suitable information system has led to the development of a methodology for endusers to develop their own applications with only the guidance of information technology professionals (ITPs) — here entitled ‘Small Unit Enduser Rapid Application Development’ or SERAD. A data base management system (DBMS) is used to manage data about ‘focal objects’ with status flags and queries/views at interface points through UDA (UserAction, DataEntry, ApplicationAction) cycles. The system which permits data entry almost immediately, not only eventually creates a full application, but also trains endusers in the process. The methodology leads ITPs and endusers through a sequence of exercises in systems analysis, tailored to minimise the time and effort input of ITPs despite the relative lack of IT training and concepts in endusers, with a view to rapidly creating dynamic, robust and sound information systems.

Strengthening the information support for decision making has been identified as an important first step toward improving the efficiency, effectiveness, and equitability of the health care system in the Philippines. A Philippine-German Cooperation is in partnership toward developing a need-responsive and cost-effective Health and Management Information System (HAMIS). Four information baskets are being strengthened specifically to address these needs in a cost-effective way: public health information systems, hospital information systems, information systems on economics and financing, information systems on good health care management. BLACKBOX is the management information system for public health programs, vital statistics, mortality and notifiable diseases of the Philippines. It handles and retrieves all data that is being collected by public health workers routinely all over the Philippines. The eventual aim of BLACKBOX is to encourage the development of an information culture in which health managers actively utilise information for rational planning and decision making for a knowledge based health care delivery.

Contemporary medical practice increasingly involves the use of inter-professional teams and complex care protocols. Increasing emphasis on value for money, medical audit, quality assurance and optimal outcomes requires that the practitioner has ready access to large amounts of up-to-date information, and that various abstracts and summaries of cases are made available quickly to providers, purchaser/funders, statisticians and researchers, and others. Rapid movements of large quantities of information is vital for the future success of health care: development of health information networks are vital strategic goals. In 1991 New Zealand initiated a widespread process of health services reform, whose success depended upon better availability and faster movements of information. The first phase of a national network to support these needs was successfully implemented in mid 1993: this provided for a point of connection for all individuals and organisations involved in the health sector, using commercial networking services. Fundamental to this development has been the adoption adaptation and development of appropriate standards and specifications for interconnection profiles, communications protocols, message formats, privacy and security requirements classification and coding systems and data element definitions. These have been selected to provide the maximum utility whilst imposing the minimum of constraints on the diversity of end user systems.

As technology transforms how information is accessed, stored and disseminated, the concept of the library changes as well. In its plans for a new building to house both library and computing services, the University of Maryland at Baltimore (UMAB) will give physical form and organizational dimensions to this new concept of the library. UMAB's library of the future will be an ‘informatics institution,’ designed to accommodate new technologies that support problem-based learning in the health sciences curricula. This new library will embody the concept and the discipline of health informatics.