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Biomedical subjects

Y M Chae

Publications and source records attributed to Y M Chae.

12 recordsLinked to original sources
PubMed1992

The development of a decision support system for diagnosing nasal allergy.

This paper deals with the problem of improving the capability of the medical decision support system (MDSS) for diagnosing nasal allergy by integrating the previously developed expert system with the neural network approach. Three knowledge acquisition methods were used to develop the expert system: statistical, rule-based, and the combined approach. Among the three, a combined approach showed the best prediction rate based on discriminant analysis. Using the results of a combined approach as input values, the neural network was developed using back-propagation method. Unlike the expert system, the neural network system provides the resulting allergy status in probabilistic terms. Managerial as well as legal issues were also discussed in this paper.

Decision Support Techniques↗
PubMed1992

Morphogenic development of the pancreas in the staged human embryo.

The Carnegie stage is widely applied in the field of human embryology, and it is more logical to analyze the embryos by this stage than CR length or menstrual age. In this study, the early development of the pancreas is studied by tissue observation and reconstruction using serial sections of 33 human embryo ranging from Carnegie stages 11 to 23. The dorsal pancreas develops from the dorsal wall of the duodenum in stage 12, and the ventral pancreas from the proximal part of the cystic primordium in stage 13 or 14 as a single epithelial thickening, but in one case, as a bilateral thickening which contains some isolated spaces. The rotation of the ventral pancreas starts in stage 15, and completes in stage 17. Surrounding connective tissue differentiates in stage 18.

Female↗
PubMed1990

The QUALCARE Scale: developing an instrument to measure quality of home care.

In previous research, the theoretical and methodological problems associated with operationalizing elder abuse have been multiple. The QUALCARE Scale was developed in response to the documented problems. The scale is an observational rating scale designed to quantify the quality of family caregiving to home-dwelling elders in six areas: physical, medical management, psychosocial, environmental, human rights and financial. The scale is a 53 item scale in a Likert type format. The QUALCARE Scale is completed by professional nurses after a nursing assessment of the degree to which the caregiver meets the needs of the elder in the six dimensions. The nursing assessment involves both observations and verbal data gathering. In this paper, the development of the scale and the methodological issues associated with scale development are discussed.

Aged↗
PubMed1990

The QUALCARE Scale: testing of a measurement instrument for clinical practice.

This article continues the discussion of the theoretical and methodological issues associated with the use of measurement instruments in nursing such as the QUALCARE Scale. The QUALCARE Scale is an observational rating scale designed to quantify the quality of family caregiving to home-dwelling elders in six areas: physical, medical management, psychosocial, environmental, human rights and financial. This manuscript continues the discussion by reporting the psychometric properties of the scale. The QUALCARE Scale was tested in a descriptive correlational study with 249 caregiver-elder dyads. The results supported evidence of interrater reliability, internal consistency, and criterion and construct validity. Three issues in the use of measurement instruments in clinical practice are discussed: (i) quantification versus qualification, (ii) clinical relevance and (iii) the establishment of rating standards.

Aged↗
PubMed1985

MEDISGRPS: a clinically based approach to classifying hospital patients at admission.

The Medical Illness Severity Grouping System--called MEDISGRPS--is an admission-oriented patient severity grouping system that uses objective, key clinical findings to place patients in one of five severity groupings. Data from five hospitals indicate that severity level at admission is an important predictor of resource use, is essential for analysis of patients who deteriorate and/or respond poorly to therapy, and is useful to further specify DRGs. Measures of effectiveness and efficiency using MEDISGRPS are suggested.

Diagnosis-Related Groups↗