Models and the Early Detection of Disease: Methodological Considerations

2002 ◽  
pp. 1-18 ◽  
Author(s):  
Marvin Zelen ◽  
Sandra J. Lee
Keyword(s):  
Early Detection ◽  
Early Detection Of Disease ◽  
Methodological Considerations

scholarly journals Using SNSs for early detection of disease outbreak in developing countries: Evidence from COVID-19 pandemic in Nigeria

Heliyon ◽  
2021 ◽  
pp. e07184
Author(s):  
Tunde Adebisi ◽  
Ayooluwa Aregbesola ◽  
Festus Asamu ◽  
Ogadimma Arisukwu ◽  
Eyitayo Oyeyipo
Keyword(s):  
Developing Countries ◽  
Early Detection ◽  
Disease Outbreak ◽  
Early Detection Of Disease

scholarly journals Experimental Ehrlichia canis infection changes acute-phase proteins

2012 ◽  
Vol 21 (3) ◽  
pp. 206-212 ◽  
Author(s):  
Thiago Demarchi Munhoz ◽  
Joice Lara Maia Faria ◽  
Giovanni Vargas-Hérnandez ◽  
José Jurandir Fagliari ◽  
Áureo Evangelista Santana ◽  
...  
Keyword(s):  
Early Detection ◽  
Early Diagnosis ◽  
Acute Phase ◽  
Acute Phase Proteins ◽  
Ehrlichia Canis ◽  
Laboratory Findings ◽  
Early Detection Of Disease ◽  
Acid Glycoprotein ◽  
The Third ◽  
Canine Ehrlichiosis

Early diagnosis of canine ehrlichiosis favors prompt institution of treatment and improves the prognosis for the animal, since this disease causes mortality among dogs. Studies have shown that determining the concentration of acute-phase proteins (APPs) may contribute towards early detection of disease and aid in predicting the prognosis. This study aimed to evaluate the APP profile in dogs experimentally infected with Ehrlichia canis, at the start of the infection and after treatment. It also investigated whether any correlation between APP levels and the clinical and laboratory alterations over the course of the disease would be possible. The results obtained showed abnormal levels of all the APPs on the third day after infection (D3), with the highest levels being reached on D18, with the exception of ceruloplasmin and acid glycoprotein, which presented their peaks on D6 and D12 respectively. We concluded that assessment of APP levels could contribute towards establishing an early diagnosis of canine ehrlichiosis, particularly regarding acid glycoprotein and ceruloplasmin, since these proteins were detected at increased levels even before the onset of clinical and laboratory findings of the disease.

scholarly journals URINE GLUCOSE DETECTION AS A DIABETES DISEASE IN WOMEN AND ELDERLY IN KEDUNGPANDAN VILLAGE, JABON, SIDOARJO

2021 ◽  
Vol 1 (1) ◽  
pp. 5-10
Author(s):  
Andreas Putro Ragil Santoso ◽  
Devyana Dyah Wulandari
Keyword(s):  
Early Detection ◽  
Community Service ◽  
Metabolic Disorders ◽  
The Elderly ◽  
Total Sample ◽  
Glucose Detection ◽  
Early Detection Of Disease ◽  
The Public

Diabetes is a disease of metabolic disorders caused by poor production of insulin by the pancreas or due to the use of body insulin which is not maximal, causing interference. The main diabetes that often occurs in the community is type 1 and type 2 diabetes because of the influence of body insulin. Examination for detection is intended so that the public can find out about the presence of glucose in the urine so that the community can immediately recover faster, considering that if there is a glucose level in the urine, there is an increase in the level of glucose in the blood. The method used in this community service is to collect residents at the center, which is then carried out by examining the urine sample using a urine dysptic. Based on the results of examinations carried out on 62 people consisting of mothers and the elderly, it showed that there were 10 positive people or 19% of the total sample. This shows that early detection is important because there are still people who do not know the importance of early detection of disease in themselves, especially in the Kedung Pandan area.

scholarly journals Role of Machine Learning Approach for Detection and Classification of Diseases in Cotton Plant

2021 ◽  
Vol 12 (5) ◽  
pp. 810-817
Author(s):  
Sandhya N. dhage, Dr. Vijay Kumar Garg
Keyword(s):  
Machine Learning ◽  
Early Detection ◽  
Cotton Plant ◽  
Early Stage ◽  
Disease Diagnosis ◽  
Learning Approach ◽  
Early Detection Of Disease ◽  
Cotton Crop ◽  
Machine Learning Approach ◽  
Crop Diseases

Qualitative and quantitative agricultural production leads to economic benefits which can be achieved by periodic monitoring of crop, detection and prevention of crop diseases and insects. Quality of crop production is reduced by pest infection and crop diseases. Existing measures involves manual detection of cotton diseases by farmers and experts which requires  regular monitoring and detection manifest at middle to later stage of infection which causes many disadvantages such as becoming  too late for diseases to be cured.  Lack of early detection of diseases causes the diseases to be spread in nearby crops in the field and also spraying of pesticides is done on entire field for minimizing the infection of disease. The main goal of proposed research topic is to find the solution to the agriculture problem which involves detecting disease in cotton plant at early stage and classify the disease based on symptoms. Early detection of disease at an early stage prevent it from spreading to another area and preventive measures can be taken by farmers by spraying pesticides to control its growth which helps to increase the cotton yield production. Automatic identification of the different diseases affecting cotton crop will give many benefits to the farmers so that time, money will be saved and also gives healthy life to the crop. The contribution of this paper is to present the machine learning approach used for cotton crop disease diagnosis and classification.

scholarly journals Loeffler’s endocarditis with isolated left ventricular involvement on cardiac MRI

2019 ◽  
Vol 12 (4) ◽  
pp. e227642 ◽  
Author(s):  
Pramod Kumar ◽  
Sheragaru Hanumanthappa Chandrashekhara ◽  
Sanjeev Kumar ◽  
Amarinder Singh Malhi
Keyword(s):  
Early Detection ◽  
Cardiac Mri ◽  
Young Male ◽  
Restrictive Cardiomyopathy ◽  
Left Ventricular ◽  
Endomyocardial Fibrosis ◽  
Early Disease ◽  
Early Detection Of Disease ◽  
The Right ◽  
Loeffler Endocarditis

Loeffler endocarditis is an uncommon restrictive cardiomyopathy associated with eosinophilia and endomyocardial fibrosis causing diastolic restriction, predominantly involving the right ventricle. Cardiac MRI plays a crucial role in early detection of disease. Early disease usually responds well to corticosteroids. We describe a case of Loeffler endocarditis with isolated left ventricular involvement on MRI in a young male having hypereosinophilia.

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