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A significant part of our knowledge is relationships between two terms. However, most of these information is documented as unstructured text in various forms, like books, online articles and webpages. Extract those information and store them in a structured database could help people utilize these information more conveniently. In this study, we proposed a novel approach to extract the relationships...
One of the major causes of death in the world is Heart Failure. This disease affects directly the heart's pumping job. Because of this perturbation, nutriments and oxygen are not well circulated and distributed. The New York Heart Association has classified this disease into four different classes based on patient symptoms. In this paper, we are using a data mining technique, more precisely a sequential...
The unprecedented interest in big data has paved way for augmented technologies. One of the major usefulness of big data is found in the field of healthcare analytics. The healthcare data come from varied sources. Specifically EHR data provide a comprehensive view of patient's health. People are paying more attention to their health and want the best possible healthcare especially with new technologies...
The heart disease describes a range of conditions affecting our heart. It can include blood vessel diseases such as coronary artery disease, heart rhythm problems or and heart defects. This term is often used for cardiovascular disease, i.e. narrowed or blocked blood vessels leading to a heart attack, chest pain or stroke. In our work, we analysed three available data sets: Heart Disease Database,...
The amount of data being collected and stored is huge and is expanding at a vivid pace at both the national and international level. Health care organizations correspondingly generate a large volume of information every day. The health care industry is rich in information but it needs to discover hidden relationships and patterns in this data. This paper intends to use data mining techniques to discover...
Heart disease is still a growing global health issue. In the health care system, limiting human experience and expertise in manual diagnosis leads to inaccurate diagnosis, and the information about various illnesses is either inadequate or lacking in accuracy as they are collected from various types of medical equipment. Since the correct prediction of a person's condition is of great importance,...
In healthcare systems, there is huge medical data collected from many medical tests which conducted in many domains. Much research has been done to generate knowledge from medical data by using data mining techniques. However, there still needs to extract hidden information in the medical data, which can help in detecting diseases in the early stage or even before happening. In this study, we apply...
Data mining is an advanced technology, which is the process of discovering actionable information from large set of data, which is used to analyze large volumes of data and extracts patterns that can be converted to useful knowledge. Medical data mining has a great potential for exploring the hidden patterns in the data sets of medical domain. These patterns can be utilized to do clinical diagnosis...
Clinical practice calls for reliable diagnosis and optimized treatment. However, human errors in health care remain a severe issue even in industrialized countries. The application of clinical decision support systems (CDSS) casts light on this problem. However, given the great improvement in CDSS over the past several years, challenges to their wide-scale application are still present, including:...
Machine learning is a subdivision of Artificial Intelligence (AI) that is concerned with the design and development of intelligent algorithms that enables machines to learn from data without being programmed. Machine learning mainly focus on how to automatically recognize complex patterns among data and make intelligent decisions. In this paper, intelligent machine learning algorithms are used to...
In this work a decision support system (DSS) for the conversion of Unified Parkinson's Disease Rating Scale (UPDRS) motor symptoms into a Hoehn & Yahr stage representation is proposed. Accurate estimation of a Parkinson's Disease patient's Hoehn & Yahr stage is of great importance since this single value is enough to represent condition, severity of symptoms and localization and disease progression...
This decision tree is normally applicable in data mining in order to produce a framework that predicts the value of object or its dependent variable, established on the various input or independent variable. CART algorithms are mainly used in Medical, Statistics etc. For heart disease patients it is complex for medical practitioners to predict the heart attack as it is a complex task that requires...
The massive amount of data collected by healthcare sector can be effective for analysis, diagnosis and decision making if it is mined properly. Hidden information extracted from the voluminous data can provide help and remedy to handle critical healthcare situations. Chronic kidney disease is a fatal illness of kidney which can be prevented with early correct predictions and proper precautions. Data...
Data mining can be used in various fields' i.e. mobile computing, web mining, expert predictions, crime analysis, engineering, management and medicine. In medical field, data mining techniques can be used by the researchers for the diagnosis and prediction of various diseases. A framework is proposed to predict Syncope Disease using Ensemble technique that contains Naïve Bayes, Gini Index and Support...
In upholding the Islamic way of life, effort to seek for moderation can be in the form of obesity prevention. Obesity is becoming the future burden of nations and actions have been taken to curb the problem of obesity. Most nations predict obesity based on the national past trend using data from population-based health surveys which are costly. Alternative method now points to data analytics which...
Indian agriculture is a toughest profession with the unpredictability of climate and weather conditions that occur every year. India recently launched INSAT 3DR, an ISRO satellite which gives a clear picture of forecasting rainfall and weather conditions to improve its support to millions of Farmers. Although these facilities are available, the crop yield in affected by the unpredicted diseases which...
Data mining is the procedure of breaking down data from unlike perspectives and resuming it into useful information. It is very important in the field of classification of the objects. It has been fruitfully applied in expert systems to get knowledge. We can determine appropriate classification of unknown objects according to decision tree rules by applying inductive methods to the given values of...
Leptospirosis is a disease that affects mainly low-income populations, with an incidence of 500,000 cases per year worldwide[1]. The disease has symptoms often confused with other febrile syndromes, such as dengue, influenza and viral hepatitis. Improved diagnosis of patients with leptospirosis is very important for health professionals, epidemiological surveillance and primarily for rapid evaluation...
Hypertension is one of the leading causes of human deaths world. Based on data from the WHO in 2013, that there are more than 17 million people worldwide died of cardiovascular disease. While in Indonesia, based on the Basic Health Research in 2013, there were 25.8 percent of Indonesia's population suffering from hypertension [1] [2]. This research is develops a system of prediction of prognosis in...
Big data is one of the latest technologies that have the potential for radically changing the way organizations use information to enhance the customer experience and transform their business models. The healthcare industry has been handling large amounts of data and is largely driven by compliance, regulatory requirements, record keeping and similar aspects of patient care. The goal is to introduce...
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