• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.92-97
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• 1995

In medical diagnostic process we are dealing with the preliminary diagnosis based on the interview chart. We will quantify the qualitative information of a patient by dual scaling and establish both prototypes of fuzzy diagnostic sets and the fuzzy linear regressions. Its utility is shown in the diagnosis of headache and CAFDDH.

• Anxiety and mood
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• v.13 no.2
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• pp.53-59
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• 2017

Reliable and valid diagnostic screening tools in the primary care setting enable accurate estimation of depression in individuals at risk or in need of treatment, and provide patients with an opportunity to receive optimal treatments. Although there have been extensive studies on screening tools for depression used in domestic mental health settings, there is little consideration and lack of a thorough review of the diagnostic validity of screening tools. In the current review, we selected 13 representative screening tools for depression which were evaluated in a total of 19 validation studies conducted in Korea. We summarized DSM-5 target domains, diagnostic indices, sensitivity, specificity, cut-off scores, and diagnostic validity information for each tool. Finally, the depression measurement expert group was constituted to evaluate the current status of screening tools for depression, and their recommendations for a new screening tool were summarized. This study was conducted as part of the Mental Health Technology Development project to develop the Korean screening tool for depression (K-DEP).

• The Journal of the Society of Korean Medicine Diagnostics
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• v.22 no.1
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• pp.19-31
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• 2018

For the purpose of the basic educated-establishment on the diagnostic methods of "facial color and shape which reflect human's spiritual essence and personality", we study on the diagnostic value and application of the human face. The study's domain is divided the form and color of human face. And the form and color of human face is respectively observed the diagnostic value and contents. The form of human face reflect plenty the information of the mankind, and the observation of the face is applied to the "Physiognomie" refering to the external features of humans. Therefore the diagnosis on the form of human face is the primary factor in the grouping of five-element human, the discrimination of the Sasang constitution, and the classification of Hyunsang type. The color of human face reflect the physical information of internal organs and the pathological change of disease, therefore we examine the region, character and grade of disease by the inspection of complexion including the changes of color and luster of the facial skin. The inspection on the color is also the primary factor in the grouping of five-element human, the classification of Hyunsang and the differentiation of syndromes. The value of the inspection of complexion including the changes of color and form of the face is widely known. In the future, we think, we need to study more about the theory of the diagnostic value and application of the human face.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.186-188
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• 2021

The architecture named IDPS is a design concept of web-based integrated platform for heterogeneous naval combat system, which accomplishes efficiency(decreasing complexity) of diagnosis process and reduces time to diagnose system. Each type of surface vessel has its own diagnostic processes and applications, and that means it also requires its own diagnostic engineer(inefficiency in human resource management). In addition, man-based diagnostic causes quality issues such as difference approach of log analysis in accordance with engineer skills. Thus In this paper, we designed integrated diagnostic platform named IDPS with simplified common process regardless of type of surface vessel and we reinforced IDPS with status decision algorithm(SDA) that judges current software status of vessel based on gathered lots of logs. It will enable engineers to diagnose system more efficiently and to use more resources in utilizing SDA-analyzed diagnostic results.

• Journal of Veterinary Clinics
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• v.25 no.3
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• pp.146-151
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• 2008

During the clinical decision making practitioners are often faced with performing diagnostic tests to solve the presenting problems seen in the patients. The diagnostic utility of a test has traditionally been described by technical terms such as sensitivity, specificity, and positive (PPV) and negative predictive value (NPV). Although well known, clinicians are frequently unclear about the concept and application of these terms in everyday evidence-based clinical decision making. Sensitivity and specificity, which are intrinsic properties of diagnostic tests, summarizes the characteristics of the test over a population. The PPV and NPV are greatly dependent on the population prevalence of disease, and thus they do not transferable to different patients or clinical settings. Besides, considering the fact that clinicians more often interested in knowing the extent to which a test result could confirm or exclude of a condition under consideration (posttest probability), these measures do not provide answers on this question. The likelihood ratios (LR) using the information contained in sensitivity and specificity are becoming increasingly popular for reporting the usefulness of diagnostic tests because this term provide an indication of posttest probability as a function of the pretest probability. In this article, clinical applications of LR are illustrated with some practical examples. Discussion is also included of the inherent limitations regarding diagnostic test characteristics.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.407-414
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• 2002

Being recently increased interests of our healthcare, a host of symptoms-diagnostic sites has been introduced on the World Wide Web. But conventional healthcare sites provide users with only a very restricted functions. In this paper, we propose the use of Artificial Neural Networks (ANNs) as a flexible symptoms-diagnostic tool that enables learning effects of ANNs (not expert's knowledge) to be incorporated into the diagnostic process. We develop a novel algorithm for predicting patient\`s disease that satisfy user (or expert)-specified symptoms on WWW. Our algorithm provides two important benefits : 1) enables users (patients) to be taken early diagnostic, and 2) enables experts to perform confidently diagnostic by referencing the predicted diseases-list with its respective possibility.

• Imaging Science in Dentistry
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• v.37 no.3
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• pp.117-126
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• 2007

Although the diagnostic information provided by radiographs may be of definite benefit to the patients, the radiographic examination does carry the potential for harm from exposure to ionizing radiation. Therefore we should try to expose radiation as low as reasonably achievable and to give diagnostic information to patients as much as possible. All of dentists should have competence in radiation protection. I wish to deal with what we should do for the optimization of radiation protection in dental clinic.

• Journal of the Korean Data and Information Science Society
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• v.6 no.1
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• pp.63-71
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• 1995

We have consider the study of local influence for smoothing parameter estimates in spline regression model with heteroscedasticity. Practically, generalized cross-validation does not work well in the presence of heteroscedasticity. Thus we have proposed the local influence measure for generalized cross-validation estimates when errors are heteroscedastic. And we have examined effects of diagnostic by above measures through Hyperinflation data.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.173-181
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• 1997

In oriental medicine, it is required that correct medical knowledge should be maintained for medical expert system which analyzes and diagnoses patients symptoms. Typical medical expert system has a knowledge base as its core, and the knowledge base contains a domain specific knowledge about patients records. However, oriental medicine diagnostic knowledge is formed mostly as qualitative data, knowledge could be ambiguous and uncertain. In this paper, we looked at quantification methods and propose a method for quantifying the oriental medicine diagnostic knowledge, which is improving the knowledge base of an oriental medicine expert system.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.97-112
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• 2000

The basic idea of case-based reasoning is to solve a new problem using the previous problem-solving experiences. In this research we develop a case-based reasoning system for equipment malfunction diagnosis. We first divide the case base into clusters using the case-based clustering technique. Then we develop an appropriate case-based diagnostic system for each cluster. In other words for individual cluster a different case-based diagnostic system which uses different weights for attributes is developed. As a result multiple case-based reasoning system are operating to solve a diagnostic problem. In comparison to the performance of the single case-based reasoning system our system reduces the computation time by 50% and increases the accuracy by 5% point.