• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.33-38
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• 2021

Recently, transfer learning techniques with a base convolutional neural network (CNN) model have widely gained acceptance in early detection and classification of crop diseases to increase agricultural productivity with reducing disease spread. The transfer learning techniques based classifiers generally achieve over 90% of classification accuracy for crop diseases using dataset of crop leaf images (e.g., PlantVillage dataset), but they have ability to classify only the pre-trained diseases. This paper provides with an evaluation scheme on selecting an effective base CNN model for crop disease transfer learning with regard to the accuracy of trained target crops as well as of untrained target crops. First, we present transfer learning models called CDC (crop disease classification) architecture including widely used base (pre-trained) CNN models. We evaluate each performance of seven base CNN models for four untrained crops. The results of performance evaluation show that the DenseNet201 is one of the best base CNN models.

• Journal of Korea Multimedia Society
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• v.25 no.11
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• pp.1653-1671
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• 2022

Crop diseases affect crop production, more than 30 billion USD globally. We proposed a classification study of crop species and diseases using deep learning algorithms for corn, cucumber, pepper, and strawberry. Our study has three steps of species classification, disease detection, and disease classification, which is noteworthy for using captured images without additional processes. We designed deep learning approach of deep learning convolutional neural networks based on Mask R-CNN model to classify crop species. Inception and Resnet models were presented for disease detection and classification sequentially. For classification, we trained Mask R-CNN network and achieved loss value of 0.72 for crop species classification and segmentation. For disease detection, InceptionV3 and ResNet101-V2 models were trained for nodes of crop species on 1,500 images of normal and diseased labels, resulting in the accuracies of 0.984, 0.969, 0.956, and 0.962 for corn, cucumber, pepper, and strawberry by InceptionV3 model with higher accuracy and AUC. For disease classification, InceptionV3 and ResNet 101-V2 models were trained for nodes of crop species on 1,500 images of diseased label, resulting in the accuracies of 0.995 and 0.992 for corn and cucumber by ResNet101 with higher accuracy and AUC whereas 0.940 and 0.988 for pepper and strawberry by Inception.

• The Korean Journal of Physiology and Pharmacology
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• v.18 no.4
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• pp.279-288
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• 2014

Ulcerative colitis and Crohn's disease are a set of chronic, idiopathic, immunological and relapsing inflammatory disorders of the gastrointestinal tract referred to as inflammatory bowel disorder (IBD). Although the etiological factors involved in the perpetuation of IBD remain uncertain, development of various animal models provides new insights to unveil the onset and the progression of IBD. Various chemical-induced colitis models are widely used on laboratory scale. Furthermore, these models closely mimic morphological, histopathological and symptomatical features of human IBD. Among the chemical-induced colitis models, trinitrobenzene sulfonic acid (TNBS)-induced colitis, oxazolone induced-colitis and dextran sulphate sodium (DSS)-induced colitis models are most widely used. TNBS elicits Th-1 driven immune response, whereas oxazolone predominantly exhibits immune response of Th-2 phenotype. DSS-induced colitis model also induces changes in Th-1/Th-2 cytokine profile. The present review discusses the methodology and rationale of using various chemical-induced colitis models for evaluating the pathogenesis of IBD.

• Journal of Preventive Medicine and Public Health
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• v.56 no.4
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• pp.291-302
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• 2023

Objectives: Disability weights require regular updates, as they are influenced by both diseases and societal perceptions. Consequently, it is necessary to develop an up-to-date list of the causes of diseases and establish a survey panel for estimating disability weights. Accordingly, this study was conducted to calculate, assess, modify, and validate disability weights suitable for Korea, accounting for its cultural and social characteristics. Methods: The 380 causes of disease used in the survey were derived from the 2019 Global Burden of Disease Collaborative Network and from 2019 and 2020 Korean studies on disability weights for causes of disease. Disability weights were reanalyzed by integrating the findings of an earlier survey on disability weights in Korea with those of the additional survey conducted in this study. The responses were transformed into paired comparisons and analyzed using probit regression analysis. Coefficients for the causes of disease were converted into predicted probabilities, and disability weights in 2 models (model 1 and 2) were rescaled using a normal distribution and the natural logarithm, respectively. Results: The mean values for the 380 causes of disease in models 1 and 2 were 0.488 and 0.369, respectively. Both models exhibited the same order of disability weights. The disability weights for the 300 causes of disease present in both the current and 2019 studies demonstrated a Pearson correlation coefficient of 0.994 (p=0.001 for both models). This study presents a detailed add-on approach for calculating disability weights. Conclusions: This method can be employed in other countries to obtain timely disability weight estimations.

• Journal of Microbiology and Biotechnology
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• v.28 no.9
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• pp.1413-1425
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• 2018

Shiga toxins (Stxs) are the main virulence factors expressed by the pathogenic Stx-producing bacteria, namely, Shigella dysenteriae serotype 1 and certain Escherichia coli strains. These bacteria cause widespread outbreaks of bloody diarrhea (hemorrhagic colitis) that in severe cases can progress to life-threatening systemic complications, including hemolytic uremic syndrome (HUS) characterized by the acute onset of microangiopathic hemolytic anemia and kidney dysfunction. Shiga toxicosis has a distinct pathogenesis and animal models of Stx-associated HUS have allowed us to investigate this. Since these models will also be useful for developing effective countermeasures to Stx-associated HUS, it is important to have clinically relevant animal models of this disease. Multiple studies over the last few decades have shown that mice injected with purified Stxs develop some of the pathophysiological features seen in HUS patients infected with the Stx-producing bacteria. These features are also efficiently recapitulated in a non-human primate model (baboons). In addition, rats, calves, chicks, piglets, and rabbits have been used as models to study symptoms of HUS that are characteristic of each animal. These models have been very useful for testing hypotheses about how Stx induces HUS and its neurological sequelae. In this review, we describe in detail the current knowledge about the most well-studied in vivo models of Stx-induced HUS; namely, those in mice, piglets, non-human primates, and rabbits. The aim of this review is to show how each human clinical outcome-mimicking animal model can serve as an experimental tool to promote our understanding of Stx-induced pathogenesis.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5655-5661
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• 2015

Purpose: To assess the role of two adjuvant chemotherapy regimens, anthracycline-based and CMF on disease free survival and overall survival breast cancer patients by meta-analysis approach in Eastern Mediterranean and Asian countries to determine which is more effective and evaluate the appropriateness and efficiency of two different proposed statistical models. Materials and Methods: Survival curves were digitized and the survival proportions and times were extracted and modeled to appropriate covariates by two multivariate mixed effects models. Studies which reported disease free survival and overall survival curves for anthracycline-based or CMF as adjuvant chemotherapy that were published in English in the Eastern Mediterranean region and Asia were included in this systematic review. The two transformations of survival probabilities (Ln (-Ln(S)) and Ln(S/ (1-S))) as dependent variables were modeled by a multivariate mixed model to same covariates in order to have precise estimations with high power and appropriate interpretation of covariate effects. The analysis was carried out with SAS Proc MIXED and STATA software. Results: A total of 32 studies from the published literature were analysed, covering 4,092 patients who received anthracycline-based and 2,501 treated with CMF for the disease free survival and in order to analyze the overall survival, 13 studies reported the overall survival curves in which 2,050 cases were treated with anthracycline-based and 1,282 with CMF regimens. Conclusions: The findings illustrated that the model with dependent variable Ln (-Ln(S)) had more precise estimations of the covariate effects and showed significant difference between the effects of two adjuvant chemotherapy regimens. Anthracycline-based treatment gave better disease free survival and overall survival. As an IPD meta-analysis in the Italy the results of Angelo et al in 2011 also confirmed that anthracycline-based regimens were more effective for survival of breast cancer patients. The findings of Zare et al 2012 on disease free survival curves in Asia also provided similar evidence.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.15 no.2
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• pp.175-190
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• 2011

Objectives: Even though there has been no consensus on the concept of viscera organ between the oriental and western medicine, we tried to investigate the correlation between clinical biomarkers of five Jang and chronological age and develop the models for predicting five Jang biological ages by statistical analysis. Methods: We obtained data from about 120,000 subjects who visited health promotion centers for health promotion and disease prevention from January 2004 to June 2009. Participants were included if they were over 20 years old, and excluded if reported to have cardiovascular disease or other serious medical illness such as cancer, malignant hypertension, uncontrolled diabetes, cardiopulmonary insufficiency, liver disease, pancreatic disease or renal disease. Among the clinical biomarkers obtained, we selected the biomarkers which were associated with the function of 5 Jang in previous studies, or showed statistically significant correlation with age. Multiple regression models were used for building prediction models of biological age after adjusting for potential confounders for men and women, respectively. Pearson correlation coefficient was calculated to examine the linear relationship between age and various biomarkers, and multiple regression analysis was used for building the prediction models of five Jang biological ages for men and women, respectively. All statistical data analysis was performed by using SPSS Version 12.0 software and statistical significance was obtained if p<0.05. Results: For males, the best models were developed using 12, 2, 8, 3, and 4 biomarkers for predicting biological ages of heart, lung, liver, pancreas, and kidney, respectively (R2 = 0.57, 0.43, 0.11, 0.24, and 0.93, respectively). Similar to males, for the females, 10, 2, 8, 3, and 4 biomarkers were selected as the models respectively (R2 = 0.76, 0.44, 0.14, 0.38, and 0.89, respectively). Conclusions: As we have developed for the first time the models for predicting five Jang biological ages with common clinical biomarkers, it is expected that these models may be used as clinical supplementary tools in the evaluation of aging status and functional decline of five Jang according to age in health promotion centers and private clinics. At the same time, it is considered that the use as objective tools to evaluate aging status and functional decline of each Jang.

• BMB Reports
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• v.52 no.6
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• pp.349-359
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• 2019

After the first research declaring the generation of human induced pluripotent stem cells (hiPSCs) in 2007, several attempts have been made to model neurodegenerative disease in vitro during the past decade. Parkinson's disease (PD) is the second most common neurodegenerative disorder, which is mainly characterized by motor dysfunction. The formation of unique and filamentous inclusion bodies called Lewy bodies (LBs) is the hallmark of both PD and dementia with LBs. The key pathology in PD is generally considered to be the alpha-synuclein (${\alpha}$-syn) accumulation, although it is still controversial whether this protein aggregation is a cause or consequence of neurodegeneration. In the present work, the recently published researches which recapitulated the ${\alpha}$-syn aggregation phenomena in sporadic and familial PD hiPSC models were reviewed. Furthermore, the advantages and potentials of using patient-derived PD hiPSC with focus on ${\alpha}$-syn aggregation have been discussed.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.211-221
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• 2024

Pakistan is a top producer and exporter of high-quality rice, but traditional methods are still being used for detecting rice diseases. This research project developed an automated rice blast disease diagnosis technique based on deep learning, image processing, and transfer learning with pre-trained models such as Inception V3, VGG16, VGG19, and ResNet50. The modified connection skipping ResNet 50 had the highest accuracy of 99.16%, while the other models achieved 98.16%, 98.47%, and 98.56%, respectively. In addition, CNN and an ensemble model K-nearest neighbor were explored for disease prediction, and the study demonstrated superior performance and disease prediction using recommended web-app approaches.

• Korean Journal of Biological Psychiatry
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• v.6 no.2
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• pp.149-152
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• 1999

Transgenic mice models of Alzheimer's disease were produced by overexpressing APP(amyloid precursor protein) mutant and presenilin mutant genes using the promotors that induced neuronal expression. The neuropathologies, electrophysiological changes and behavioral changes that were demonstrated in these transgenic mice models were amyloid changes, gliotic changes, A-beta increases, deficit in LTP(long-term potentiation) and behavioral changes. Some or all of the above changes were found in each transgenic mice model. These models generally showed amyloid neuropathology but they usually lacked the neurofibrillary tangles. So, they can be regarded as partial models of Alzheimer's disease. The development of them is undoubtedly the great progress toward future research.