• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.36 no.3
• /
• pp.109-117
• /
• 2013

This study designed a "Diagnostic Model for Management Innovation of Medium Enterprises" based on the theoretical background of success factor and management diagnosis model for management innovation of medium enterprises and suggested a measure for utilization of strategic subject and diagnostic model that enterprises can apply. Utilization of medium enterprises management innovation diagnostic model designed through this study would be of help for making a diagnosis of the capability maturity level of enterprises' current management system and improving it by establishing a challenging capability objective and building a circulation system capable of innovating enterprises. It is expected for enterprises to overcome growing pains and establish a management system capable of achieving outcome (productivity) by repeating measurement and innovation through management diagnosis. In addition, this study provides a method to produce a strategic subject, select priority of implementation and prepare an implementation road map by classifying and filtering management issues produced as a result of management diagnosis in a systematic way. If variables necessary for production of an objective weighted value of scoring and discover of elements for category of diagnostic model and elementary items as well as design of a self-diagnosis questionnaire, measurement of management outcome suggested in this study can be able to be verified and supplemented through case study in the future, it is expected to make the degree of completion as a diagnostic model elevated that may help for growth and development through innovation of medium enterprises.

• Korean Journal of Radiology
• /
• v.22 no.4
• /
• pp.612-623
• /
• 2021

Objective: To evaluate the diagnostic performance of a deep learning algorithm for the automated detection of developmental dysplasia of the hip (DDH) on anteroposterior (AP) radiographs. Materials and Methods: Of 2601 hip AP radiographs, 5076 cropped unilateral hip joint images were used to construct a dataset that was further divided into training (80%), validation (10%), or test sets (10%). Three radiologists were asked to label the hip images as normal or DDH. To investigate the diagnostic performance of the deep learning algorithm, we calculated the receiver operating characteristics (ROC), precision-recall curve (PRC) plots, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) and compared them with the performance of radiologists with different levels of experience. Results: The area under the ROC plot generated by the deep learning algorithm and radiologists was 0.988 and 0.988-0.919, respectively. The area under the PRC plot generated by the deep learning algorithm and radiologists was 0.973 and 0.618-0.958, respectively. The sensitivity, specificity, PPV, and NPV of the proposed deep learning algorithm were 98.0, 98.1, 84.5, and 99.8%, respectively. There was no significant difference in the diagnosis of DDH by the algorithm and the radiologist with experience in pediatric radiology (p = 0.180). However, the proposed model showed higher sensitivity, specificity, and PPV, compared to the radiologist without experience in pediatric radiology (p < 0.001). Conclusion: The proposed deep learning algorithm provided an accurate diagnosis of DDH on hip radiographs, which was comparable to the diagnosis by an experienced radiologist.

• Nuclear Medicine and Molecular Imaging
• /
• v.41 no.3
• /
• pp.201-208
• /
• 2007

Purpose: We investigated whether the diagnostic performance of SPECT scintimammography (SMM) can be improved by adding computer-aided diagnosis (CAD) of ultrasonography (US). Materials and methods: We reviewed breast SPECT SMM images and corresponding US images from 40 patients with breast masses (21 malignant and 19 benign tumors). The quantitative data of SPECT SMM were obtained as the uptake ratio of lesion to contralateral normal breast. The morphologic features of the breast lesions on US were extracted and quantitated using the automated CAD software program. The diagnostic performance of SPECT SMM and CAD of US alone was determined using receiver operating characteristic (ROC) curve analysis. The best discriminating parameter (D-value) combining SPECT SMM and the CAD of US was created. The sensitivity, specificity and accuracy of combined two diagnostic modalities were compared to those of a single one. Results: Both SPECT SMM and CAD of US showed a relatively good diagnostic performance (area under curve = 0.846 and 0.831, respectively). Combining the results of SPECT SMM and CAD of US resulted in improved diagnostic performance (area under curve =0.860), but there was no statistical differerence in sensitivity, specificity and accuracy between the combined method and a single modality. Conclusion: It seems that combining the results of SPECT SMM and CAD of breast US do not significantly improve the diagnostic performance for diagnosis of breast cancer, compared with that of SPECT SMM alone. However, SPECT SMM and CAD of US may complement each other in differential diagnosis of breast cancer.

• Journal of Genetic Medicine
• /
• v.8 no.1
• /
• pp.28-34
• /
• 2011

Most clinicians understand clinical trials as the evaluation process for new medicine before their use. However, clinical trials can also be applied to laboratory diagnostic tests (LDTs) to verify diagnostic accuracy and efficacy before their clinical laboratory implementation for patients. The clinical trial of LDT has two distinctive characteristics that are different from the case of pharmaceuticals and thus worth special consideration. One of them is the level of evidence. The well-designed randomized controlled trials (RCTs) are known to provide the best evidence to prove the clinical efficacy of any pharmaceutical products. However, RCTs lose practicality when applied to LDTs due to various issues including ethical complications. For this reason, comparative study format is considered more feasible approach for LDTs. In addition pharmaceuticals and LDTs are different in that the user's intervention is not required for the former but critical to the latter. Moreover, in the case of pharmaceuticals, end-products are produced by manufacturers before being used by clinicians. However, in LDTs, once reagents and instruments are provided by manufacturers, they are first utilized by clinical laboratories to produce test results in order for clinicians to use them later. In other words, when it comes to LDTs, clinical laboratories play the role of manufacturers, providing reliable test results with improved quality assurance. Considering the distinctive characteristics of LDTs, we would like to offer detailed suggestions to successfully perform clinical trials in LDTs, which include analytical performance measures, clinical test performance measures, diagnostic test accuracy measures, clinical effectiveness measures, and post-implementation surveillance.

• Korean Journal of Radiology
• /
• v.22 no.8
• /
• pp.1240-1252
• /
• 2021

Objective: To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT and digital mammography (DM), and the use of DM alone through a systematic review and meta-analysis. Materials and Methods: Ovid-MEDLINE, Ovid-Embase, Cochrane Library and five Korean local databases were searched for articles published until March 25, 2020. We selected studies that reported diagnostic accuracy in women who were recalled after screening or symptomatic. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to estimate pooled sensitivity and specificity. We compared the diagnostic accuracy between DBT and DM alone using meta-regression and subgroup analyses by modality of intervention, country, existence of calcifications, breast density, Breast Imaging Reporting and Data System category threshold, study design, protocol for participant sampling, sample size, reason for diagnostic examination, and number of readers who interpreted the studies. Results: Twenty studies (n = 44513) that compared DBT and DM alone were included. The pooled sensitivity and specificity were 0.90 (95% confidence interval [CI] 0.86-0.93) and 0.90 (95% CI 0.84-0.94), respectively, for DBT, which were higher than 0.76 (95% CI 0.68-0.83) and 0.83 (95% CI 0.73-0.89), respectively, for DM alone (p < 0.001). The area under the summary receiver operating characteristics curve was 0.95 (95% CI 0.93-0.97) for DBT and 0.86 (95% CI 0.82-0.88) for DM alone. The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses. Conclusion: Use of DBT was more accurate than DM alone for the diagnosis of breast cancer. Women with clinical symptoms or abnormal screening findings could be more effectively evaluated for breast cancer using DBT, which has a superior diagnostic performance compared to DM alone.

• Journal of Communications and Networks
• /
• v.13 no.2
• /
• pp.149-159
• /
• 2011

In this paper, we study the problem of how to design a medical-grade wireless local area network (WLAN) for healthcare facilities. First, unlike the IEEE 802.11e MAC, which categorizes traffic primarily by their delay constraints, we prioritize medical applications according to their medical urgency. Second, we propose a mechanism that can guarantee absolute priority to each traffic category, which is critical for medical-grade quality of service (QoS), while the conventional 802.11e MAC only provides relative priority to each traffic category. Based on absolute priority, we focus on the performance of real-time patient monitoring applications, and derive the optimal contention window size that can significantly improve the throughput performance. Finally, for proper performance evaluation from a medical viewpoint, we introduce the weighted diagnostic distortion (WDD) as a medical QoS metric to effectively measure the medical diagnosability by extracting the main diagnostic features of medical signal. Our simulation result shows that the proposed mechanism, together with medical categorization using absolute priority, can significantly improve the medical-grade QoS performance over the conventional IEEE 802.11e MAC.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.24 no.9
• /
• pp.1157-1165
• /
• 2000

A classic examples of the abnormal combustions are the knock and misfire, which raise noxious performance and life of the engine. A heavy knock can also cause severe damages to the engine itself, which gives more reason why it must be detected and corrected. With the response of the today's requirements, we have researched the new diagnostic system which uses the breakdown voltage characteristics between electrodes of spark plug. This breakdown voltage depends on the pressure, temperature and even the shape and material of electrodes. But there is no data of breakdown voltage in case of using the spark plug as a electrodes. So, in this study, we show the breakdown voltage characteristic by pressure and temperature in constant volume bomb, which will make it possible to diagnose the engine combustion phenomenon.

• Journal of Biomedical Engineering Research
• /
• v.13 no.1
• /
• pp.69-78
• /
• 1992

This Paper describes implementation of a remote ECG diagnostic system using telephone line. The overall system includes ECG data acquisition system, ECG terminal, system control software, automatic diagnosis system, and transmission system.'The proposed system provides various functions, which are ECG data acquisition, transmission, receiving, diagnosis and dialogue between patients and medical doctors. Thls system is very simple and convienient to use. We evaluate the performance of modem and the accuracy of automatic diagnosis algorithm. The obtained results suggest the Possibilities of a remote ECG diagnostic system using the only existed telephone line.

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

• Proceedings of the KOSOMBE Conference
• /
• v.1994 no.12
• /
• pp.26-27
• /
• 1994

The first step implementation of a hospital-wide Picture Archiving Communications System (PACS) at a newly built hospital Samsung Medical Center (SMC), is described. Current clinical operation encompasses the fiber optics delivery of direct-interfaced magnetic resonance imager (LRI), X-ray computed tomography (CT). digital subtraction angiography (DSA) and computed radiography (CR) digital images via high performance file server to the departments of radiology, neurosurgery, orthopedics surgery, neurology, emergency room and the surgical intensive care unit.