• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.4
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• pp.259-265
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• 2016

In this paper, new method was proposed to classify lung tissues such as Broncho vascular, Emphysema, Ground Glass Reticular, Ground Glass, Honeycomb, Normal for early lung disease detection. 459 Statistical features was extraced from joint histogram matrix based on multi resolution analysis, volumetric LBP, and CT intensity, then dominant features was selected by using adaboost learning. Accuracy of proposed features and 3D AMFM was 90.1% and 85.3%, respectively. Proposed joint histogram based features shows better classification result than 3D AMFM in terms of accuracy, sensitivity, and specificity.

• The Korean Journal of Nuclear Medicine
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• v.37 no.1
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• pp.13-23
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• 2003

Neurodegenerative disorders cause a variety of dementia including Alzheimer disease, frontotemporal dementia, dementia with Lewy bodies, corticobasal degeneration, progressive supranuclear palsy, and Huntington's disease. PET scan is useful for early detection and differential diagnosis of these dementing disorders. Also, it provides valuable information about clinico-anatomical correlation, allowing better understanding of function of brain. Here we discuss recent achievements PET studies regarding these dementing disorders. Future progress in PET technology, new tracers, and image analysis will play an important role in further clarifying the disease pathophysiology and brain functions.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1250-1257
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• 2020

The early detection of diseases is important in agriculture because diseases are major threats of reducing crop yield for farmers. The shape and color of plant leaf are changed differently according to the disease. So we can detect and estimate the disease by inspecting the visual feature in leaf. This study presents a vision-based leaf classification method for detecting the diseases of tomato crop. ResNet-50 model was used to extract the visual feature in leaf and classify the disease of tomato crop, since the model showed the higher accuracy than the other ResNet models with different depths. We propose a new ensemble approach using several DCNN classifiers that have the same structure but have been trained at different ranges in the DCNN layers. Experimental result achieved accuracy of 97.19% for PlantVillage dataset. It validates that the proposed method effectively classify the disease of tomato crop.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.275-279
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• 2023

Throughout the 20th century, the transition of pig farms from extensive to intensive commercial operations amplified the risk of disease transmission, particularly involving African swine fever (ASF). Real-time temperature monitoring systems have emerged as essential tools for early ASF diagnosis. In this paper, we introduce new real-time temperature monitoring ear tags (RTMEs) modeled after existing ear tag designs. Our crafted Pig-Temp platforms have three primary advantages. First, they can be effortlessly attached to pig ears, ensuring superior compatibility. Second, they enable real-time temperature detection, and the data can be displayed on a personal computer or smartphone application. Furthermore, they demonstrate excellent measurement accuracy, ranging from 98.9% to 99.8% at temperatures between 2.2 and 360℃. A linear regression approach enables fever symptoms associated with ASF to be identified within 3 min using RTMEs. The communication range extends to approximately 12 m (452 m²), enabling measurements from an estimated 75 to 2,260 pigs per gateway. These newly developed Pig-Temp platforms offer singifcant enhancement of early ASF detection.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.23 no.3
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• pp.276-285
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• 2020

Purpose: Non-alcoholic fatty liver disease (NAFLD) ranges in severity from simple steatosis to steatohepatitis. Early detection of NAFLD is important for preventing the disease from progressing to become an irreversible end-stage liver disease. We developed a nomogram that allows for non-invasive screening for NAFLD in obese children. Methods: Anthropometric and laboratory data of 180 patients from our pediatric obesity clinic were collected. Diagnoses of NAFLD were based on abdominal ultrasonographic findings. The nomogram was constructed using predictors from a multivariate analysis of NAFLD risk factors. Results: The subjects were divided into non-NAFLD (n=67) and NAFLD groups (n=113). Factors, including sex, body mass index, abdominal circumference, blood pressure, insulin resistance, and levels of aspartate aminotransferase, alanine aminotransferase (ALT), γ-glutamyl transpeptidase (γGT), uric acid, triglycerides, and insulin, were significantly different between the two groups (all p<0.05) as determined using homeostatis model assessment of insulin resistance (HOMA-IR). In our multivariate logistic regression analysis, elevated serum ALT, γGT, and triglyceride levels were significantly related to NAFLD development. The nomogram was established using γGT, uric acid, triglycerides, HOMA-IR, and ALT as predictors of NAFLD probability. Conclusion: The newly developed nomogram may help predict NAFLD risk in obese children. The nomogram may also allow for early NAFLD diagnosis without the need for invasive liver biopsy or expensive liver imaging, and may also allow clinicians to intervene early to prevent the progression of NAFLD to become a more advanced liver disease.

• Korean Journal of Bronchoesophagology
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• v.7 no.2
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• pp.161-167
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• 2001

Background and Objectives： Total laryngectomy is often required for advanced cases. But this operation induced the many inconvenience of basic daily life. Early diagnosis of laryngeal cancer is very important to prevent from this disastrous condition. In this point of view, mass screening test for early detection of laryngeal cancer is necessary. Screening test using voice has many advantages such as simple, less interventional. Voice collection by Automatic Response System(ARS) is comfortable and easy to got acoustic sample. Thus author tried to got the acoustic parameters which can differentiate normal, benign. and malignant laryngeal diseases and also checked the availability of parameters on neural network system. Materials and Methods: Author has evaluated the voice from 17 laryngeal cancer patients and 45 benign laryngeal disease patients who visited at Department of Otolaryngology, Pusan National University Hospital from May 1998 to April 2001, and 15 normal control. Author chose the sir Parameters (Jitt. vFo, Shim, vAm, NHR, SPI) that was thought to be related with voice collected by ARS among thirty-three parameters analysed by a Multi-Dimensional Voice Program (MDVP). Two-step neural network was used for the availability of six parameters. Results: The detection rate of normal voice by ARS voice analysis is 78.5% and detection rate of abnormal voice was 97.1 o/o. Among abnormal voice, the detection rate of benign laryngeal diseases and laryngeal cancers were 82.4 o/o, 70.6% respectively. Conclusion: Author concluded that six parameters and Matlab based neural network software may be effective in development of acoustic screening system for laryngeal cancer and further study should be necessary for development of new acoustic parameters.

• Journal of Gastric Cancer
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• v.22 no.4
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• pp.306-318
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• 2022

Gastric cancer (GC) is associated with high morbidity and mortality rates. Thus, early diagnosis is important to improve disease prognosis. Endoscopic assessment represents the most reliable imaging method for GC diagnosis; however, it is semi-invasive and costly and heavily depends on the skills of the endoscopist, which limit its clinical applicability. Therefore, the search for new sensitive biomarkers for the early detection of GC using noninvasive sampling collection methods has attracted much attention among scientists. Urine is considered an ideal biofluid, as it is readily accessible, less complex, and relatively stable than plasma and serum. Over the years, substantial progress has been made in screening for potential urinary biomarkers for GC. This review explores the possible applications and limitations of urinary biomarkers in GC detection and diagnosis.

• IMMUNE NETWORK
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• v.24 no.2
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• pp.12.1-12.17
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• 2024

Exosomes are double phospholipid membrane vesicles that are synthesized and secreted by a variety of cells, including T cells, B cells, dendritic cells, immune cells, are extracellular vesicles. Recent studies have revealed that exosomes can play a significant role in under both physiological and pathological conditions. They have been implicated in regulation of inflammatory responses, immune response, angiogenesis, tissue repair, and antioxidant activities, particularly in modulating immunity in autoimmune diseases (AIDs). Moreover, variations in the expression of exosome-related substances, such as miRNA and proteins, may not only offer valuable perspectives for the early warning, and prognostic assessment of various AIDs, but may also serve as novel markers for disease diagnosis. This article examines the impact of exosomes on the development of AIDs and explores their potential for therapeutic application.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.7
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• pp.4369-4371
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• 2013

Objective: To evaluate the association of a diagnosis of lung cancer and combined detection of serum carcinoembryonic antigen (CEA), carbohydrateantigen 19-9 (CA19-9), neuron specific enolase (NSE) as well as the cytokeratin 19 fragment (CYFRA21-1). Methods: Serum CEA, CA19-9, NSE and CYFRA21-1 were assessed in 150 patients with lung cancer, 100 patients with benign lung disease and 100 normal control subjects, and differences of expression were compared in each group, and joint effects of these tumor markers in the diagnosis of lung cancer were analyzed. Results: Serum CEA, CA19-9, NSE and CYFRA21-1 in patients with lung cancer were significantly higher than those with benign lung disease and normal controls (p<0.01). It is suggested that these four tumor markers combined together could produce a positive detection rate of 90.2%, significantly higher than that of any single test. Conclusion: Combination detection of CEA, CA19-9, NSE and CYFRA21-1 could significantly improve the sensitivity and specificity in diagnosis of lung cancer, and could be important in early detection.

• BMB Reports
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• v.36 no.4
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• pp.399-402
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• 2003

Early detection of bladder cancer is particularly important since it dramatically affects the survival rates. However, neither urinary cytology nor tumor markers that are currently used are sensitive enough for the early detection of bladder cancer or recurrent disease. The ras genes are frequently mutated in cancer. In this study, we investigated the diagnostic potential of ras mutation analysis in urinary sediments of patients with bladder cancer using a single-strand conformation polymorphism analysis and polymerase chain reaction. Mutation in codon 12 of the H-ras gene was observed in 39% of the patients. Our results indicate that this approach may significantly improve diagnostic sensitivity in detecting bladder tumors.