• 대한세포병리학회지
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• 제18권2호
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• pp.93-99
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• 2007

Fine needle aspiration has been widely used to diagnose of breast lesions whether they are malignant or not. When applied by experienced and well-trained practitioners, its accuracy can approach that of histopathology. In order to make optimal use of FNAB in breast lesions, this article has reviewed the criteria for sample adequacy, the diagnostic terminology and the cytomorphologic approach to making a diagnosis and avoiding diagnostic pitfalls.

• Korean Journal of Radiology
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• 제23권9호
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• pp.901-910
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• 2022

Objective: This study aimed to assess the technical feasibility, efficacy, and safety of the safe triangular working zone (STWZ) approach applied in percutaneous vertebroplasty (PV) for spinal metastases involving the posterior part of the vertebral body. Materials and Methods: We prospectively enrolled 87 patients who underwent PV for spinal metastasis involving the posterior part of the vertebral body, with or without the STWZ approach, from January 2019 to April 2022. Forty-nine patients (27 females and 22 males; mean age ± standard deviation [SD], 57.2 ± 11.6 years; age range, 31-76 years) were included in group A (with STWZ approach), accounting for 54 vertebrae. Thirty-eight patients (18 females and 20 males; 59.1 ± 10.9 years; 29-81 years) were included in group B (without STWZ approach), accounting for 57 vertebrae. Patient demographics, procedure-related variables, and pain relief as assessed using the visual analog scale (VAS) were collected at different time points. Tumor recurrence in the vertebrae after PV was analyzed using Kaplan-Meier curves. Results: The STWZ approach was successful from T1 to L5 without severe complications. Cement filling was satisfactory in 47/54 (87.0%) and 25/57 (43.9%) vertebrae in groups A and B, respectively (p < 0.001). Cement leakage was not significantly different between groups A and B (p = 1.000). Mean VAS score ± SD before and 1 week and 1, 3, 6, 9, and 12 months after PV were 7.6 ± 1.8, 4.2 ± 2.0, 2.7 ± 1.9, 1.9 ± 1.5, 1.7 ± 1.4, 1.7 ± 1.1, and 1.6 ± 1.3, respectively, in group A and 7.2 ± 1.7, 4.0 ± 1.3, 3.4 ± 1.6, 2.4 ± 1.2, 1.8 ± 1.0, 1.4 ± 0.5, and 1.7 ± 0.9, respectively, in group B. Kaplan-Meier analysis showed a lower tumor recurrence rate in group A than in group B (p = 0.001). Conclusion: The STWZ approach may represent a new, safe, alternative/auxiliary approach to target the posterior part of the vertebral body in the PV for spinal metastases.

• Korean Journal of Radiology
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• 제22권2호
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• pp.198-212
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• 2021

Placenta accreta spectrum (PAS) is an abnormal placental adherence or invasion of the myometrium or extrauterine structures. As PAS is primarily staged and managed surgically, imaging can only guide and facilitate diagnosis. But, imaging can aid in preparations for surgical complexity in some cases of PAS. Ultrasound remains the imaging modality of choice; however, magnetic resonance imaging (MRI) is required for evaluation of areas difficult to visualize on ultrasound, and the assessment of the extent of placenta accreta. Numerous MRI features of PAS have been described, including dark intraplacental bands, placental bulge, and placental heterogeneity. Failure to diagnose PAS carries a risk of massive hemorrhage and surgical complications. This article describes a comprehensive, step-by-step approach to diagnostic imaging and its potential pitfalls.

• 대한산업공학회지
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• 제30권1호
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• pp.44-49
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• 2004

The aim of this study is to compare the methods in analyzing bio-signals representing measure driver's psychophysiological staus. This study has considered three approaches: first, the deterministic approach calculating the mean and standard deviation of bio-signal, second, probabilistic approach converting driver's bio-signal values to probability density function and identifying individual state relative to overall distribution, and third, diagnostic approach identifying the pattern change of signal over certain period of time. For evaluation of analysis methods, driver's bio-signal was collected under various road conditions, and three analysis approaches were applied respectively. In result, the deterministic approach was found to be simple to use, but generated a large variability of bio-signal. The probabilistic approach provide a relative status of individual driver among overall population, but too much affected by temporal variability of individual driver. The diagnostic approach seemed to reasonably find driver's psychophysiological change over certain period of time, but still needs to develop quantification method of the bio-signal.

• Nuclear Engineering and Technology
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• 제56권2호
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• pp.558-567
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• 2024

Diagnostic support systems are being researched to assist operators in identifying and responding to abnormal events in a nuclear power plant. Most studies to date have considered single abnormal events only, for which it is relatively straightforward to obtain data to train the deep learning model of the diagnostic support system. However, cases in which multiple abnormal events occur must also be considered, for which obtaining training data becomes difficult due to the large number of combinations of possible abnormal events. This study proposes an approach to maintain diagnostic performance for multiple abnormal events by training a deep learning model with data on single abnormal events only. The proposed approach is applied to an existing algorithm that can perform feature selection and multi-label classification. We choose an extremely randomized trees classifier to select dedicated monitoring parameters for target abnormal events. In diagnosing each event occurrence independently, two-channel convolutional neural networks are employed as sub-models. The algorithm was tested in a case study with various scenarios, including single and multiple abnormal events. Results demonstrated that the proposed approach maintained diagnostic performance for 15 single abnormal events and significantly improved performance for 105 multiple abnormal events compared to the base model.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• 제24권1호
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• pp.1-6
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• 2021

Next-generation sequencing (NGS) technologies have changed the process of genetic diagnosis from a gene-by-gene approach to syndrome-based diagnostic gene panel sequencing (DPS), diagnostic exome sequencing (DES), and diagnostic genome sequencing (DGS). A priori information on the causative genes that might underlie a genetic condition is a prerequisite for genetic diagnosis before conducting clinical NGS tests. Theoretically, DPS, DES, and DGS do not require any information on specific candidate genes. Therefore, clinical NGS tests sometimes detect disease-related pathogenic variants in genes underlying different conditions from the initial diagnosis. These clinical NGS tests are expensive, but they can be a cost-effective approach for the rapid diagnosis of rare disorders with genetic heterogeneity, such as the glycogen storage disease, familial intrahepatic cholestasis, lysosomal storage disease, and primary immunodeficiency. In addition, DES or DGS may find novel genes that that were previously not linked to human diseases.

• Korean Journal of Radiology
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• 제20권6호
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• pp.939-946
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• 2019

Objective: To report our initial experience of percutaneous sacroplasty (PSP) with an interpedicular approach for treating painful sacral metastases involving multiple sacral vertebral bodies. Materials and Methods: This study prospectively enrolled 10 consecutive patients (six men and four women; mean age, 56.3 ± 13.8 years) who underwent PSP for painful sacral metastases involving multiple sacral vertebral bodies from March 2017 to September 2018. Visual analogue scale (VAS) scores, Oswestry disability index (ODI) values, and the number of opioids prescribed to the patients were assessed before and after PSP. The procedure duration, length of hospitalization, and complications were also recorded. Results: Mean VAS and ODI declined significantly from 6.90 ± 1.20 and 74.40 ± 5.48 before the procedure to 2.70 ± 1.34 and 29.60 ± 14.57 after the procedure, respectively (p < 0.01). The median number of opioids prescribed per patient decreased from 2 (interquartile range [IQR] 1-3) pre-procedure to 1 (IQR 0-3) post-procedure (p < 0.01). Nine of the 10 patients showed no or decreased opioid usage, and only 1 patient showed unchanged usage. The mean procedure duration was 48.5 ± 3.0 minutes. The average length of hospitalization was 4.7 ± 1.7 days. Extraosseous cement leakage occurred in three cases without causing any clinical complications. Conclusion: PSP with an interpedicular approach is a safe and effective treatment in patients with painful sacral metastases involving multiple sacral vertebral bodies and can relieve pain and improve mobility.

• Clinical and Experimental Pediatrics
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• 제50권2호
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• pp.127-131
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• 2007

Fever of unknown origin (FUO) has been a convenient term used to classify patients who warrant a particular systemic approach to diagnostic evaluation and management. The greatest clinical concern in evaluating FUO is identifying patients whose fever has a serious or life-threatening cause when a delay in diagnosis could jeopardize successful intervention. Thorough history and complete physical examination are critical to uncover the etiologic diagnosis. Most cases of FUO in children are caused by atypical presentations of common diseases rather than by typical manifestations of rare disorders. Selection of diagnostic tests and speed of investigation should be guided by a knowledge of the disease severity, patient age, epidemiologic and geographic information, and any positive findings from a detailed history and physical examination. The three most common causes of FUO in children are infectious diseases, connective tissue diseases, and malignancy. In general, the prognosis of FUO in children is better than that of adults. Although the outcome is dependent on the primary disease process, fever abates spontaneously in most cases in whom the cause of fever remains unclear.

• Journal of Information Processing Systems
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• 제18권6호
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• pp.822-829
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• 2022

According to existing study into the remote fault diagnosis procedure, the current diagnostic approach has an imperfect decision model, which only supports communication in a close distance. An Internet of Things (IoT)-based remote fault diagnostic approach for wind power equipment is created to address this issue and expand the communication distance of fault diagnosis. Specifically, a decision model for active power coordination is built with the mechanical energy storage of power generation equipment with a remote diagnosis mode set by decision tree algorithms. These models help calculate the failure frequency of bearings in power generation equipment, summarize the characteristics of failure types and detect the operation status of wind power equipment through IoT. In addition, they can also generate the point inspection data and evaluate the equipment status. The findings demonstrate that the average communication distances of the designed remote diagnosis method and the other two remote diagnosis methods are 587.46 m, 435.61 m, and 454.32 m, respectively, indicating its application value.

• Transactions on Control, Automation and Systems Engineering
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• 제1권1호
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• pp.54-61
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. By using the FCM, authors have proposed FCM-based fault diagnostic algorithm. However, it can offer multiple interpretations for a single fault. In process engineering, as experience accumulated, some form of quantitative process knowledge is available. If this information can be integrated into the FCM-based fault diagnosis, the diagnostic resolution can be further improved. The purpose of this paper is to propose an enhanced FCM-based fault diagnostic scheme. Firstly, the membership function of fuzzy set theory is used to integrate quantitative knowledge into the FCM-based diagnostic scheme. Secondly, modified TAM recall procedure is proposed. Considering that the integration of quantitative knowledge into FCM-based diagnosis requires a great deal of engineering efforts, thirdly, an automated procedure for fusing the quantitative knowledge into FCM-based diagnosis is proposed by utilizing self-learning feature of neural network. Finally, the proposed diagnostic scheme has been tested by simulation on the two-tank system.