• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.147-153
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• 2018

In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.

• Molecules and Cells
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• v.28 no.3
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• pp.195-200
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• 2009

Protein tyrosine kinases (PTKs) play a central role in the modulation of a wide variety of cellular events such as differentiation, proliferation and metabolism, and their unregulated activation can lead to various diseases including cancer and diabetes. PTKs represent a diverse family of proteins including both receptor tyrosine kinases (RTKs) and non-receptor tyrosine kinases (NRTKs). Due to the diversity and important cellular roles of PTKs, accurate classification methods are required to better understand and differentiate different PTKs. In addition, PTKs have become important targets for drugs, providing a further need to develop novel methods to accurately classify this set of important biological molecules. Here, we introduce a novel statistical model for the classification of PTKs that is based on their structural features. The approach allows for both the recognition of PTKs and the classification of RTKs into their subfamilies. This novel approach had an overall accuracy of 98.5% for the identification of PTKs, and 99.3% for the classification of RTKs.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.923-935
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• 2022

This paper deals with detection and classification of leaf diseases for phenomics systems. As the smart farm systems of plants are increased, It is important to determine quickly the abnormal growth of plants without supervisors. This paper considers the color distribution and shape information of leaf diseases, and designs two deep leaning networks in training the leaf diseases. In the first step, color distribution of input image is analyzed for possible diseases. In the second step, the image is first partitioned into small segments using mean shift clustering, and the color information of each segment is inspected by the proposed Color Network. When a segment is determined as disease, the shape parameters of the segment are extracted and inspected by proposed Shape Network to classify the leaf disease types in the third step. According to the experiments with two types of diseases (frogeye/rust and tipburn) for apple leaves and iceberg, the leaf diseases are detected with 92.3% recall for a segment and with 99.3% recall for an input image where there are usually more than two disease segments. The proposed method is useful for detecting leaf diseases quickly in the smart farm environment, and is extendible to various types of new plants and leaf diseases without additional learning.

• Journal of Korean Neurosurgical Society
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• v.67 no.3
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• pp.308-314
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• 2024

Vein of Galen aneurysmal malformation is one of important pediatric arteriovenous shunt diseases, especially among neonates and infants. Here, early history of the disease identification, basic pathoanatomy with a focus on the embryonic median prosencephalic vein, classification and differential diagnoses, and recent genetic studies are reviewed.

• Journal of the Korean Society of Safety
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• v.26 no.5
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• pp.110-117
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• 2011

The paper tries to understand the other side of characteristics on occupational injuries and diseases in forestry. Occupational injuries and diseases in forestry seems to be greatly influenced by the environmental characteristics of the mountain district and individual's ability of workers. A traditional method on the analysis of occupational injuries and diseases data may show that the main cause of occupational injuries and diseases is the material factors significantly. To identify the other side of occupational injuries and diseases in forestry, the occupational injuries and diseases data of 3,091 workers in forestry was analyzed. The data in forestry, 2009 shows certain characteristics among the recent occupational injuries and diseases data. The first step is to classify the data according to standard of classification of original cause materials. Material factors are 72.3% and human factors (included managerial factors) and environmental factors are 27.0%. The next step is to reclassify the first step data by using the concept of influence factors which caused and influenced occupational injuries and diseases. The result is that material factors are 2.4%, human factors(included managerial factors) and environmental factors are 97.0%. Also, an aging degree of workers in forestry is higher than other categories of business. It is true that an aging degree of injured or diseased workers in forestry is higher than that of other categories of business. However, relevance with increase of occupational injuries and diseases could not be explained. An injury and disease rate in forestry is remarkably increased recently than other categories of business. One of the reason why an injury and disease rate increased remarkably in 2009 could be considered as the increase of the number of workers and related budget. Therefore, this study proposes important measures or means to prevent occupational injuries and diseases in forestry.

• The Journal of Internal Korean Medicine
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• v.42 no.4
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• pp.510-531
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• 2021

Objectives: The purpose of this study was to review the status of numeric rating scale (NRS) usage and suggest the potential for use in multicenter retrospective studies of various diseases. Methods: Articles published from 2011 to 2021 that used the keywords "NRS", "Multi-center", and "RCT" were identified in foreign databases, including EMBASE, PubMed, CENTRAL. The articles were analyzed according to their use of "NRS" by symptoms and by disease group using the major classifications of the Korean Standard Classification of Diseases (KCD-7). Results: Classification by symptom in a total of 288 articles illustrates that the NRS was not only commonly used in pain evaluation but also for non-pain symptoms. In usage with non-pain symptoms, chief complaint of patients was the most common at 79%, and other factors included treatment satisfaction, evaluation of daily life, and sleep quality. In disease classification according to the KCD-7, the NRS was commonly used in connection with musculoskeletal and connective tissue diseases but was also utilized in various other disease groups. Conclusions: This study confirms usage of the NRS in multi-center RCTs, as the NRS was widely used in all types of diseases and symptoms. Considering the result and the advantages of the NRS, it is recommended for use as a daily evaluation tool for the collection of common data in multicenter retrospective studies.

• Journal of Biomedical Engineering Research
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• v.44 no.3
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• pp.167-175
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• 2023

Chest PA is the basic examination of radiographic imaging. Moreover, Chest PA's demands are constantly increasing because of the Increase in respiratory diseases. However, it is not meeting the demand due to problems such as a shortage of radiological technologist, sexual shame caused by patient contact, and the spread of infectious diseases. There have been many cases of using artificial intelligence to solve this problem. Therefore, the purpose of this research is to build an artificial intelligence dataset of Chest PA and to find a posture evaluation method. To construct the posture dataset, the posture image is acquired during actual and simulated examination and classified correct and incorrect posture of the patient. And to evaluate the artificial intelligence posture method, a posture estimation algorithm is used to preprocess the dataset and an artificial intelligence classification algorithm is applied. As a result, Chest PA posture dataset is validated with in over 95% accuracy in all artificial intelligence classification and the accuracy is improved through the Top-Down posture estimation algorithm AlphaPose and the classification InceptionV3 algorithm. Based on this, it will be possible to build a non-face-to-face automatic Chest PA examination system using artificial intelligence.

• Childhood Kidney Diseases
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• v.16 no.1
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• pp.21-31
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• 2012

Focal segmental glomerulosclerosis (FSGS) is the name of the primary glomerular disease as well as the terminology to describe the secondary phenomena of any other glomerular diseases. It is characterized by sclerosis, hyalinosis, foam cell infiltration, vacuolar change of podocytes, and halo formation in the glomerulus. Throughout the interstitium, lymphocytes infiltration, tubular atrophy and vascular changes are accompanied. Occasionally, IgM and/or C3 depositions are noted in the sclerotic areas. Electron microscopically, diffuse effacement of foot processes are seen in non-sclerotic area like minimal change disease. Podocyte injury patterns including vacuolar changes are frequently examined. Recently, Columbia group has suggested morphologic classification of FSGS and they demonstrated very good prognosis of tip lesion and poor prognosis of both collapsing and cellular types. However, the pathogenetic classification has been suggested by others; hyperfilteration, podocyte injury, genetic lesions etc. Further studies are necessary to understand and treat this disease.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.449-453
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• 2014

Chronic diseases including hypertension and its complications are major sources causing the national medical expenditures to increase. We aim to predict the risk of hypertension complications for hypertension patients, using the sample national healthcare database established by Korean National Health Insurance Corporation. We apply classification techniques, such as logistic regression, linear discriminant analysis, and classification and regression tree to predict the hypertension complication onset event for each patient. The performance of these three methods is compared in terms of accuracy, sensitivity and specificity. The result shows that these methods seem to perform similarly although the logistic regression performs marginally better than the others.

• Korean Journal of Acupuncture
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• v.31 no.3
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• pp.108-116
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• 2014

Objectives : The purpose of this study is to identify changes of texts by investigating similarities and differences of the third chapter of limb diseases section between Beijiqianjinyaofang(BJQJYF) and Sunzhenrenqianjinfang(SZRQJF). Methods : I reviewed the third chapter of limb diseases section both of BJQJYF and SZRQJF and analysed the changes of texts. Results : 1. Hand, shoulder and low back pains mentioned in the second chapter of glossopathy from SZRQJF were moved to the third chapter of limb diseases in BJQJYF. 2. Inappropriate indications were changed reasonably. 3. Contents related with treatment were revised, by addition or deletion of contents. 4. There were some contents which were worth clinically in SZRQJF. 5. The rule of choosing acupoints for hand, arm, leg, knee and limb disease was selection of local points, and for shoulder and low back disease was selection of distant points. Conclusions : Classification and contents of the third chapter of limb diseases were re-organized systematically through proofreading by medical printing authority. However, some contents deleted from SZRQJF were worth clinically, and more studies are necessary to identify the reason why the indication and selection of acupoints were changed by proofreading.