• Journal of applied mathematics & informatics
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• v.40 no.5_6
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• pp.1151-1165
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• 2022

Key drive of information quarrying is to digest liked information starting possible information. With the colossal amount of realities kept in documents, information bases, and stores, in the medical care area, it's inexorably significant, assuming excessive, arising compelling resources aimed at examination besides comprehension like information on behalf of the withdrawal of gen that might assistance in independent direction. Classification is method in information mining; it's characterized as per private, passing on item toward a specific course established happening it is likeness toward past instances of different substances trendy the data collection. In pre-owned recycled four Classification algorithm that incorporate Multi-Layer perception, KSTAR, Bayesian Network and PART to fabricate the grouping replicas arranged the malaria data collection and analyze the replicas, degree their exhibition through Waikato Environment for Knowledge Analysis introduced to Java Development Kit 8, then utilizations outfit's technique trendy promoting presentation of the arrangement methodology. The outcome perceived that Bayesian Network return most elevated exactness of 50.05% when working on followed by Multi-Layer perception, with 49.9% when helping is half, then, at that point, Kstar with precision of 49.44%, 49.5% when supporting individually and PART have lesser precision of 48.1% when helping, The exploration recommended that Bayesian Network is awesome toward remain utilized on Malaria data collection in our sanatoriums.

• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.119-134
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• 2021

Lung cancer is one of the leading causes of cancer deaths in the world. Investigation of mortality rates is pivotal to adequately understand the determinants causing this disease, allocate public health resources, and apply different control measures. Our study aims to analyze and forecast age-specific US lung cancer mortality trends. We report functions of mortality rates for different age groups by incorporating functional principal component analysis to understand the underlying mortality trend with respect to time. The mortality rates of lung cancer have been higher in men than in women. These rates have been decreasing for all age groups since 1990 in men. The same pattern is observed for women since 2000 except for the age group 85 and above. No significant changes in mortality rates in lower age groups have been reported for both gender. Lung cancer mortality rates for males are relatively higher than females. Ten-year predictions of mortality rates depict a continuous decline for both gender with no apparent change for lower age groups (below 40).

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.149-158
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• 2022

The pandemic of Covid-19 (Coronavirus Disease 19) has devastated the world, affected millions of people, and disrupted the world economy. The cause of the Covid19 epidemic has been identified as a new variant known as Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV2). It motives irritation of a small air sac referred to as the alveoli. The alveoli make up most of the tissue in the lungs and fill the sac with mucus. Most human beings with Covid19 usually do no longer improve pneumonia. However, chest x-rays of seriously unwell sufferers can be a useful device for medical doctors in diagnosing Covid19-both CT and X-ray exhibit usual patterns of frosted glass (GGO) and consolidation. The introduction of deep getting to know and brand new imaging helps radiologists and medical practitioners discover these unnatural patterns and pick out Covid19-infected chest x-rays. This venture makes use of a new deep studying structure proposed to diagnose Covid19 by the use of chest X-rays. The suggested model in this work aims to predict and forecast the patients at risk and identify the primary COVID-19 risk variables

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.1-9
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• 2024

Predicting the spread of COVID-19 remains a challenge due to the complexity of the disease and its evolving nature. This study presents an integrated approach using the classic SIR model for infectious diseases, enhanced by the chemical master equation (CME). We employ a Monte Carlo method (SSA) to solve the model, revealing unique aspects of the SARS-CoV-2 virus transmission. The study, a first of its kind in Korea, adopts a step-by-step and complementary approach to model prediction. It starts by analyzing the epidemic's trajectory at local government levels using both basic and stochastic SIR models. These models capture the impact of public health policies on the epidemic's dynamics. Further, the study extends its scope from a single-infected individual model to a more comprehensive model that accounts for multiple infections using the jump SIR prediction model. The practical application of this approach involves applying these layered and complementary SIR models to forecast the course of the COVID-19 epidemic in small to medium-sized local governments, particularly in Gangnam-gu, Seoul. The results from these models are then compared and analyzed.

• Korean Journal Plant Pathology
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• v.3 no.3
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• pp.210-216
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• 1987

A computer program written to predict blast occurrence based on micro climatic events was developed and tested as an on-site microcomputer in field plots in 1984 and 1985. A microcomputer unit operating on alkaline batteries; continuously monitored air temperature, leaf wetness, and relative humidity; interpreted the microclimate information in relation to rice blast development and displayed daily values (0-8) of blast units of severity (BUS). Cumulative daily BUS values (CBUS) were highly correlated with blast development on the two susceptible cultivars, M-201 and Brazos grown in field plots. When CBUS values were used to predict the logit of disease proportions, the average coefficients of determination $(R^2)$ between these two factors were 71 to $91\%$, depending on cultivar and year. This was a significant improvement when compared to 61 to $79\%$ when days were used as a predictor of logit disease severity. The ability of CBUS to predict logit disease severity was slightly less with Brazos than M-201. This is significant inasmuch as Brazos showed field resistance at mid-sea­son. The results in this study indicate that the model has the potential for future use and that the model could be improved by incorporating other variables associated with host plants and pathogen races in addition to the key environmental variables.

• Research in Plant Disease
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• v.25 no.4
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• pp.196-204
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• 2019

Rice panicle blast occurred severely in southern provinces of Korea in 2014. The proportion of panicle blast incidence area to cultivated area of rice were 11.0% and 14.6% in Jeollanam-do and Gyeongsangnam-do, respectively. To identify the causal factors of the outbreak, we investigated weather conditions in August, amount of cultivated area of mainly grown cultivars, and nitrogen contents in plants with different disease incidences in 2014. 'Saenuri,' 'Ilmibyeo,' 'Unkwang,' 'Dongjin 1 ho,' 'Nampyeongbyeo,' and 'Hwangkeumnuri' were mainly grown cultivars. Monthly average of daily air temperature in August 2014 was 3.2℃ and 3.1℃ less than 2018 in Haenam and Miryang, respectively. Rainfall in August 2014 was 70.0% and 42.0% greater than 2018 in Haenam and Miryang, respectively. The numbers of blast warning days in August calculated nationwide using a forecast model for blast infection were higher in 2014 than in 2018, and they were in high level throughout the country in 2014. Nitrogen contents in plant samples from high-incidence plots were significantly higher than those from low-incidence plots. Consequently, excessive use of nitrogen fertilizers was the main factor for the disease outbreak at the level of specific farms, in addition to the collective cultivation of susceptible cultivar, low temperatures and frequent rainfalls in August.

• The Plant Pathology Journal
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• v.26 no.1
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• pp.17-24
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• 2010

A logistic model for describing combined effects of both temperature and wetness period on appressorium formation was developed using laboratory data on percent appressorium formation of Colletotrichum acutatum. In addition, the possible use of the logistic model for forecasting infection risks was also evaluated as compared with a first-order linear model. A simplified equilibrium model for enzymatic reactions was applied to obtain a temperature function for asymptote parameter (A) of logistic model. For the position (B) and the rate (k) parameters, a reciprocal model was used to calculate the respective temperature functions. The nonlinear logistic model described successfully the response of appressorium formation to the combined effects of temperature and wetness period. Especially the temperature function for asymptote parameter A reflected the response of upper limit of appressorium formation to temperature, which showed the typical temperature response of enzymatic reactions in the cells. By having both temperature and wetness period as independent variables, the nonlinear logistic model can be used to determine the length of wetness periods required for certain levels of appressorium formation under different temperature conditions. The infection model derived from the nonlinear logistic model can be used to calculate infection risks using hourly temperature and wetness period data monitored by automated weather stations in the fields. Compared with the nonlinear infection model, the linear infection model always predicted a shorter wetness period for appressorium formation, and resulted in significantly under- and over-estimation of response at low and high temperatures, respectively.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6929-6934
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• 2014

Background: To analyze the mortality distribution of esophageal cancer in China from 1991 to 2012, to forecast the mortality in the future five years, and to provide evidence for prevention and treatment of esophageal cancer. Materials and Methods: Mortality data for esophageal cancer in China from 1991 to 2012 were used to describe its epidemiological characteristics, such as the change of the standardized mortality rate, urban-rural differences, sex and age differences. Trend-surface analysis was used to study the geographical distribution of the mortality. Curve estimation, time series, gray modeling, and joinpoint regression were used to predict the mortality for the next five years in the future. Results: In China, the incidence rate of esophageal cancer from 2007 and the mortality rate of esophageal cancer from 2008 increased yearly, with males at $8.72/10^5$ being higher than females, and the countryside at $15.5/10^5$ being higher than in the city. The mortality rate increased from age 45. Geographical analysis showed the mortality rate increased from southern to eastern China, and from northeast to central China. Conclusions: The incidence rate and the standardized mortality rate of esophageal cancer are rising. The regional disease control for esophageal cancer should be focused on eastern, central and northern regions China, and the key targets for prevention and treatment are rural men more than 45 years old. The mortality of esophageal cancer will rise in the next five years.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2785-2791
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• 2014

Aims: To analyze time-dependent changes in female breast cancer (BC) mortality in China, forecast the trend in the ensuing 5 years, and provide recommendations for prevention and management. Materials and Methods: Mortality data of breast cancer in China from 1991 to 2011 was used to describe characteristics and distribution, such as the changes of the standardized mortality rate, urban-rural differences and age differences. Trend-surface analysis was used to study the geographical distribution of mortality. In addition, curve estimation, time series modeling, Gray modeling (GM) and joinpoint regression were performed to estimate and predict future trends. Results: In China, the mortality rate of breast cancer has increased yearly since 1991. In addition, our data predicted that the trend will continue to increase in the ensuing 5 years. Rates in urban areas are higher than those in rural areas. Over the past decade, all peak ages for death by breast cancer have been delayed, with the first death peak occurring at 55 to 65 years of age in urban and rural areas. Geographical analysis indicated that mortality rates increased from Southwest to Northeast and from West to East. Conclusions: The standardized mortality rate of breast cancer in China is rising and the upward trend is predicted to continue for the next 5 years. Since this can cause an enormous health impact in China, much better prevention and management of breast cancer is needed. Consequently, disease control centers in China should place more focus on the northeastern, eastern and southeastern parts of China for breast cancer prevention and management, and the key population should be among women between ages 55 to 65, especially those in urban communities.

• Journal of Preventive Medicine and Public Health
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• v.48 no.4
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• pp.203-215
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• 2015

Objectives: This study was performed to investigate the relationship between the incidence of national notifiable infectious diseases (NNIDs) and meteorological factors, air pollution levels, and hospital resources in Korea. Methods: We collected and stored 660 000 pieces of publicly available data associated with infectious diseases from public data portals and the Diseases Web Statistics System of Korea. We analyzed correlations between the monthly incidence of these diseases and monthly average temperatures and monthly average relative humidity, as well as vaccination rates, number of hospitals, and number of hospital beds by district in Seoul. Results: Of the 34 NNIDs, malaria showed the most significant correlation with temperature (r=0.949, p<0.01) and concentration of nitrogen dioxide (r=-0.884, p<0.01). We also found a strong correlation between the incidence of NNIDs and the number of hospital beds in 25 districts in Seoul (r=0.606, p<0.01). In particular, Geumcheon-gu was found to have the lowest incidence rate of NNIDs and the highest number of hospital beds per patient. Conclusions: In this study, we conducted a correlational analysis of public data from Korean government portals that can be used as parameters to forecast the spread of outbreaks.