• The Plant Pathology Journal
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• 제17권6호
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• pp.368.4-369
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• 2001

• 한국정보컨버전스학회:학술대회논문집
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• 한국정보컨버전스학회 2008년도 International conference on information convergence
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• pp.191-194
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• 2008

SNP(Single Nucleotide Polymorphism) refers to the difference in a base pair existed in DNAs of individuals. Each of it appears per 1,000 bases in human genome and it enables each gene to defer in junctions, interacts with each other to make different shapes of humans, and produces different disease sensitivities. In this paper, we propose a system to forecast lung cancer sensitivities using SNP data related with the lung cancer. A lung cancer sensitivity forecasting model is also constructed through analysis of genetic and non-genetic factors for squamous cell carcinomas, adeno carcinomas, and small cell carcinomas that may frequently appear in Korean. The proposed system with the model gives the probabilities of the onset of lung cancers in the experimental subjects.

• Genomics & Informatics
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• 제19권1호
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• pp.11.1-11.8
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• 2021

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020-December 31, 2020 and January 20, 2020-January 31, 2021) and testing data (January 1, 2021-February 28, 2021 and February 1, 2021-February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values' comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.

• 한국환경농학회지
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• 제33권1호
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• pp.52-56
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• 2014

BACKGROUND: It is known that impacts of climate change on damage occurrence by insect pests and diseases are increasing. The negative effects of climate change on production will threaten our food security. It is needed that on the basis of analysis of the impacts, proper strategies in response to climate change are developed. METHODS AND RESULTS: The objective of this paper is to estimate impacts of climate change on rice damage occurrence by insect pests and diseases, using the panal model which analyzes both cross-section data and time series data. The result of an analysis on impacts of climate change on rice damage occurrence by pest insect and disease showed that the damage occurrence by Rice leaf roller and Rice water weevil increased if temperature increased, and damage occurrence by Stripe, Sheath blight, and Leaf Blast increased if precipitation(or amount of sunshine) increased(or decreased). CONCLUSION: Adaptation strategies, supplying weather forecasting information by region, developing systematical strategies for prevention of damage occurrence by pest insect and disease, analyzing the factors of damage occurrence by unexpected pest insect and disease, enforcing international cooperation for prevention of damage occurrence are needed to minimize the impacts of damage occurrence on rice production.

• The Plant Pathology Journal
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• 제24권1호
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• pp.46-51
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• 2008

With the goal of achieving better integrated pest management for hot pepper, a disease-forecasting system was compared to a conventional disease-control method. Experimental field plots were established at Asan, Chungnam, in 2005 to 2006, and hourly temperature and leaf wetness were measured and used as model inputs. One treatment group received applications of a protective fungicide, dithianon, every 7 days, whereas another received a curative fungicide, dimethomorph, when the model-determined infection risk (IR) exceeded a value of 3. In the unsprayed plot, fruits showed 18.9% (2005) and 14.0% (2006) anthracnose infection. Fruits sprayed with dithianon at 7-day intervals had 4.7% (2005) and 15.4% (2006) infection. The receiving model-advised sprays of dimethomorph had 9.4% (2005) and 10.9% (2006) anthracnose infection. Differences in the anthracnose levels between the conventional and model-advised treatments were not statistically significant. The efficacy of 10 (2005) and 8 (2006) applications of calendar-based sprays was same as that of three (2005 and 2006) sprays based on the disease-forecast system. In addition, we found much higher the IRs with the leaf wetness sensor from the field plots comparing without leaf wetness sensor from the weather station at Asan within 10km away. Since the wetness-periods were critical to forecast anthracnose in the model, the measurement of wetness-period in commercial fields must be refined to improve the anthracnose-forecast model.

• 한국정보통신학회논문지
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• 제20권8호
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• pp.1460-1465
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• 2016

오늘날 많은 비용이 국가 의료보장체계의 유지를 위협하고 있다. 국가 질병 통제 및 방지 센터의 감사체계를 동반한 건강관리 역학성에 대한 연구에도 불구하고, 시간 한계, 표본 한계, 대상 질병 한계에 대한 제약이 여전히 존재하고 있다. 이러한 배경에서, 방대한 양의 전수 데이터를 활용하여, 많은 기술들이 건강의 선제적 예측이나 그 대상 질병을 확장하는 분야에 충분하게 적용되고 있다. 우리는 국민건강보험의 구조적 데이터와 소셜네트워크서비스의 비구조적 데이터를 활용하여 질병을 예측하는 모형을 설계하였다. 이 모형은 건강예보서비스를 제공함으로써, 국민건강을 증진시키고 사회적 혜택을 극대화할 수 있다. 또한, 빅데이터 분석에 근거하여, 건강보험비용의 갑작스러운 증가를 감소시키거나 적시적인 질병발생을 예측할 수도 있다. 관련된 의료 예측 사례를 살펴보았고, 제안된 모형의 검증을 위하여 시범과제를 통한 실험을 수행하였다.

• 대한방사선기술학회지:방사선기술과학
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• 제39권3호
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• pp.353-359
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• 2016

본 연구는 부산 경남지역에서 담낭용종의 위험인자 및 초음파영상의 형태학적 분포를 알아보고자 하였다. 실험 대상은 2016년 1월~5월까지 부산 P병원 내원환자의 복부초음파 영상을 대상으로 하였다. 그 중 복부초음파와 혈청학적 검사를 동시에 실시한 399명을 대상으로 위험인자를 분석하였다. 담낭용종 위험인자들의 통계분석은 독립표본 t검정(independent t-test)과 카이제곱 검정(chi-square test)을 시행하였다. 차이검정 결과를 고려하여 독립변수에 대한 상대 위험비(odds ratio, OR) 산출을 위해 다중 로지스틱 회귀분석(multiple logistic regression analysis)을 시행하여 변수들로부터 예측모형을 산정하여 타당성을 검정하였다. 그 결과 담낭용종 위험인자로 남성, HBsAg 양성, 중성지방이 관련이 있음을 알 수 있었다. 담낭용종의 위험인자로 확인된 남성, HBsAg 양성, 중성지방으로 예측모형 및 예측 확률값을 산정하였다. 예측확률의 민감도 61.0%, 특이도 76.8%를 보였으며, ROC 곡선의 AUC 결과는 0.735를 보여 예측모형의 타당성을 확인할 수 있었다. 복부 초음파검사 상 관찰되는 담낭용종의 형태학적 분석 결과는 고 에코, 유경, 균질한 형태가 가장 많은 분포(27.5%)를 나타내었으며, 용종 개수는 2개(38%), 크기는 5~10 mm (53%)로 가장 많았다. 담낭용종과 관련된 간질환으로는 mild fatty liver (23%), diffuse hepatopathy (21%)로 나타났다.

• Journal of Preventive Medicine and Public Health
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• 제53권3호
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• pp.158-163
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• 2020

Objectives: In the current early phase of the coronavirus disease 2019 (COVID-19) outbreak, Bali needs to prepare to face the escalation of cases, with a particular focus on the readiness of healthcare services. We simulated the future trajectory of the epidemic under current conditions, projected the impact of policy interventions, and analyzed the implications for healthcare capacity. Methods: Our study was based on the first month of publicly accessible data on new confirmed daily cases. A susceptible, exposed, infected, recovered (SEIR) model for COVID-19 was employed to compare the current dynamics of the disease with those predicted under various scenarios. Results: The fitted model for the cumulative number of confirmed cases in Bali indicated an effective reproduction number of 1.4. Interventions have decreased the possible maximum number of cases from 71 125 on day 86 to 22 340 on day 119, and have prolonged the doubling time from about 9 days to 21 days. This corresponds to an approximately 30% reduction in transmissions from cases of mild infections. There will be 2780 available hospital beds, and at the peak (on day 132), the number of severe cases is estimated to be roughly 6105. Of these cases, 1831 will need intensive care unit (ICU) beds, whereas the number of currently available ICU beds is roughly 446. Conclusions: The healthcare system in Bali is in danger of collapse; thus, serious efforts are needed to improve COVID-19 interventions and to prepare the healthcare system in Bali to the greatest extent possible.

• 디지털콘텐츠학회 논문지
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• 제16권3호
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• pp.417-424
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• 2015

산업의 고도화 및 새로운 기계의 도입, 화학물질 사용 등 산업재해의 다양한 양상과 더불어 생산설비들의 자동화, 대형화로 인해 산업재해 발생의 양상이 점차 다양해지고 있다.국내 산업재해는 OECD(Organization for Economic Cooperation and Development) 경제협력개벌기구대비, 상대적 하위수준에 있어 기업 발생 산업재해는 근로자들의 심리적 및 치료와 보상 손실에도 타격이 되어 기업 총 생산과 이윤 추구에도 중요문제가 야기되고 있다. 더불어, 장애자와 사망유족들의 증가로 생활 안정문제 등 사회적 문제도 제기된다. 이러한 동기에서 본 논문은 산업재해 통계와 산재예방사업을 분석하고, 시스템다이내믹스 법론을 이용하여 산업재해율을 예측하고 평가하는 모델을 개발하였다. 모델은 근로자수 모델, 재해자수 모델, 재해율 모델 등 총 12개의 모델로 구성되었고, 규모별 분석에서는 근로자수를 기준으로 12개 그룹으로, 업종별 분석에서는 제조업, 건설업 등 총 10개의 업종으로 구분하여 개발하였다. 개발된 모델을 토대로 업종별 규모별 산업재해율을 예측하고 산재예방사업을 다각도로 평가하는 방법론을 제시하였다.

• Journal of Preventive Medicine and Public Health
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• 제53권6호
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• pp.387-396
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• 2020

Objectives: The lack of advance planning in a public health emergency can lead to wasted resources and inadvertent loss of lives. This study is aimed at forecasting the needs for healthcare resources following the expansion of the coronavirus disease 2019 (COVID-19) outbreak in the Republic of Kazakhstan, focusing on hospital beds, equipment, and the professional workforce in light of the developing epidemiological situation and the data on resources currently available. Methods: We constructed a forecast model of the epidemiological scenario via the classic susceptible-exposed-infected-removed (SEIR) approach. The World Health Organization's COVID-19 Essential Supplies Forecasting Tool was used to evaluate the healthcare resources needed for the next 12 weeks. Results: Over the forecast period, there will be 104 713.7 hospital admissions due to severe disease and 34 904.5 hospital admissions due to critical disease. This will require 47 247.7 beds for severe disease and 1929.9 beds for critical disease at the peak of the COVID-19 outbreak. There will also be high needs for all categories of healthcare workers and for both diagnostic and treatment equipment. Thus, Republic of Kazakhstan faces the need for a rapid increase in available healthcare resources and/or for finding ways to redistribute resources effectively. Conclusions: Republic of Kazakhstan will be able to reduce the rates of infections and deaths among its population by developing and following a consistent strategy targeting COVID-19 in a number of inter-related directions.