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Cardiovascular disease (CVD) is one of the major cause of death in the recent days. The diabetes patients are mostly affected by Cardiovascular disease. An abnormal respiratory rate, heart rate, blood pressure are habitually fundamental sign of CVD. The occurrence of CVD leads to sudden death. So it is need to predict the CVD earlier. The best method of prediction is by using PPG signal. The measurement...
The goal of the paper is to demonstrate the beneficial effects obtained by associating antioxidants in the complex therapy of the metabolic syndrome. We used dedicated software instrument for automatic classification named decision tree in order to prove that. The data taken from 60 patients were grouped in two clusters and the accuracy recognition rate obtained was of 95%.
Complex problems in various disciplines like biology, medicine, humanities, management studies and so on gives various research dimensions in soft computing. Risk classification is one of the thrust areas in the field of medicine. This research work aims in risk classification of diabetic nephropathy using fuzzy logic. Fuzzy logic which is a component of soft computing is used for classification....
This paper aims to conduct the empirical analysis of reasons why e-Health effects on treatment days of patients with lifestyle-related diseases. Statistical analysis practiced based on panel data of medical expenditures of about 400 individuals from 2002 to 2006 in Nishi-aizu Town, Fukushima Prefecture, Japan. Nishi-aizu Town is one of the earliest cases in Japan to introduce e-Health successfully...
Diabetic kidney disease is a significant complication of type 2 diabetes mellitus and has a significant impact on quality of life and patient survival, both due to progression towards endstage kidney disease and associated atherosclerosis. Identification of the risk factors, especially in incipient kidney disease, is an important focus of research. The aim of our study was to rank the risk factors...
In this paper, we present a knowledge-based decision system for healthcare. It not only performs intelligent diagnoses but also produces inferential advices for the interrelated diseases involving overweight or obese, diabetes, high blood pressure and high cholesterol conditions. Moreover, it performs deep diagnoses for the pregnant Asian women; for the unknown type of diabetes and for the risk of...
This research uses association rule generation and classification techniques to support decision making, by considering a data set of diabetes type 1 & type 2 patients. There are advanced and reliable data mining techniques which leads to the discovery of unseen and useful information. The main focus of this research is to identify the yet undiscovered decision factors of diabetes which increases...
Health indicators express remarkable gaps in health systems at a world-wide level. Countries of all over the world are implementing new strategies, methodologies and technologies to better serve the millions of patients, who demand better medical attention. The current system, which is archaic and not very systematic, widens the gap even more than the quality of medical services that should be provided...
This research paper uses association rules and classification techniques to extract undiscovered information of diabetes. Previous phase of this research included the preliminary results of some undiscovered decision factors and side effects of diabetes, by considering diabetes type 1 and type 2 patients' data set. Advanced and reliable data mining techniques are used throughout this research to the...
Coronary heart disease (CHD) is one of the major causes of disability in adults as well as one of the main causes of death in the developed countries. Although significant progress has been made in the diagnosis and treatment of CHD, further investigation is still needed. The objective of this study was to develop a data-mining system for the assessment of heart event-related risk factors targeting...
Self-monitoring of blood glucose is an integral part of diabetes care which may be extended to other biometrics. Cellular and short range communication technologies will be important for the routine usage of these systems. However, the issues of follow-up and patient compliance with these emerging systems have not been yet studied evaluated but could be critical to the adoption of these technologies...
The use of mobile technologies for self-monitoring of blood glucose and blood pressure for diabetes patients is becoming increasingly popular worldwide. This is propelled by the proliferation of the wider usage of mobile phones and other wireless technologies and computing platforms in the healthcare sector. Such technologies can play a pivotal role in chronic disease management and patient self-care...
There are numerous challenges confronting the healthcare systems of Caribbean countries. The public healthcare systems in the region currently face a crisis due to factors such as shortages of medical staff, lack of proper facilities, and insufficient funding. Therefore, new approaches to managing healthcare and promoting healthier lifestyle practices are needed to address this problem. This paper...
The availability of mobile healthcare systems is increasing in demand. The world's population today is faced with many health challenges all of which require the patient to be more empowered and monitor his own health. This research focuses on some of the mobile healthcare systems available for the monitoring of two chronic non-communicable diseases: diabetes and hypertension. The study investigates...
We describe our experiences of using remote patient monitoring to support the long term management and clinical intervention in patients with chronic disease, such as CHF. Within the project we developed new algorithms to determine from vital signs collected on a daily basis, those patients requiring clinical investigation for their condition. Our aim was for patients to achieve and sustain clinically...
Autonomic nervous system dysfunction is common in patients with chronic kidney disease (CKD) and is associated with adverse cardiovascular (CV) outcomes and mortality in non-CKD populations, but has not previously been shown to predict all cause mortality in CKD. 134 patients were recruited to an observational study. CV structure, function and inflammatory status were quantified. Survival was assessed...
In this work we analyzed the T wave width evolution on an ECG database containing 27 records coming from diabetic patients performing the Valsalva Maneuver (VM). The objective is to assess whether the maneuver is accompanied with early signs of ischemia and if those are measurable by T wave shortening. The hypothesis for this T wave shortening is that endocardial action potentials reduce their duration...
First results and methods of assessment used in the application of the AEDMI project structured medical interview in a sample of 824 patients are reported. The sensitivity, specificity, and predictivity of the most frequent signs and symptoms with regard to the diagnosis of high blood pressure have been computed. Positive predictivities between 2% and 40% were found. The diagnostic value of these...
A physiological system sometimes includes oscillations as part of the control function. By using entrainment techniques and suitable frequency analysis of periodic body signals, it is possible to obtain valuable information on the autonomic system and body control mechanism in health and disease. A description is given of an integrated entrainment system using a thermal, respiration, and blood-pressure...
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