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The chest X-ray is one of the most commonly accessible radiological examinations for screening and diagnosis of many lung diseases. A tremendous number of X-ray imaging studies accompanied by radiological reports are accumulated and stored in many modern hospitals Picture Archiving and Communication Systems (PACS). On the other side, it is still an open question how this type of hospital-size knowledge...
The main purpose of outlier detection algorithms is to find a new feature that is distinct from the other features of the vector in the analyzed data set. This paper concerns outlier detection in medical databases, and the supervised and unsupervised methods used in detection of outliers in medical data are discussed. Moreover, the author's original method for detecting outliers based on linguistic...
The number of biological databases available both in the public domain and in private keep on increasing every day. Scientists and researchers need to analyze and make use of the data stored in different databases. One limitation is that these databases are stored in diverse formats. However, semantic web methods have introduced the Resource description format (RDF) to unify heterogeneous databases...
The present day world has been experiencing rapid technological advancement on the one hand and an ever increasing number of diseases afflicting the human beings on the other. To deal with the later, medical devices are innovated and introduced in to the market (making use of the technological advancements), on a continuous basis across the world. However, introducing an innovated medical device to...
The diagnostic errors are a controversial but real-life topic considered a leading cause of death and unintended harm due to medical-care procedures. We proposed a formula to assess the possibility to identify the diagnostic errors using a database analysis of patients admitted and released from the Clinic of Pulmonary Diseases. We built a database from the admittances and releases during a 21 months...
Diabetes is one of the most common metabolic diseases and the statistics show that one in eleven adults has diabetes, but one in two adults with diabetes is undiagnosed, and in 2040 one in 10 adults will have diabetes. In this paper is proposed a hybrid Adaptive Neuro-Fuzzy Inference System (ANFIS) model for classifying patients with diabetes based on data sets with diabetic patients (Pima Indians...
In this paper, we describe a cloud platform for health care tourism of Hainan province, China. The relevant business process is designed in a way that the characteristics of health care are taken into account. A scheme that combines medical tourism with a self-health care system and a nursing system is proposed. The data storage structure of the health care system is given, together with the specific...
Discovering the pathological mechanism of genetic disease is a challenging task, but has great medical significance. In this paper, a novel method to identify the pathological mechanism of the genetic disease was proposed. To validate the validity of the method, as an example, we applied the method to discovery the pathological mechanism of the human Retinitis Pigmentosa by using the gene sequencing...
Objectives: This study aimed to systematize current evidence of technologies for ageing in place designed to support the daily living of community-dwelling older adults. Methods: A systematic review of reviews and meta-analysis was performed based on a search of the literature. Results: A total of 24 reviews and meta-analysis were retrieved and interventions related to physical activity, nutrition...
The microbial diversity and taxonomic profiles of human microbiome carries indicative signals associated with several complex human diseases. Methods quantifying and differentiating profiles belonging to healthy/disease microbiomes have a potential to be used as non-invasive diagnostic tools. 16S rRNA sequencing is a currently popular and feasible technology to generate the required data for such...
This paper presents a novel approach based on the analysis of genetic variants from publicly available genetic profiles and the manually curated database, the National Human Genome Research Institute Catalog. Using data science techniques, genetic variants are identified in the collected participant profiles and then indexed as risk variants in the National Human Genome Research Institute Catalog...
Risk assessment of rare and complex diseases such as Neuroblastoma requires an efficient management of interdisciplinary data. Recent advances in genomic testing are revealing new diagnosis targets whose storage and analysis is becoming a big challenge. The use of Conceptual Models (CM) defining and structuring Neuroblastoma domain serves as a basis to determine the information required for diagnosing...
In their mission of collecting, analyzing and disseminating statistic data, the National Institutes of Statistics are more and more confronted with personal data management. With the advent of the “Open Data” [1], the need for data diffusion and to establish a link between databases created during the surveys and censuses, are necessary for planning, monitoring and activities evaluation, in a context...
The exponential growth of high dimensional biological data has led to a rapid increase in demand for automated approaches for knowledge production. Existing methods rely on two general approaches to address this challenge: 1) the Theorydriven approach, which utilizes prior accumulated knowledge, and 2)the Data-driven approach, which solely utilizes the data to deduce scientific knowledge. Both of...
The aging world population is a challenge for global healthcare. Caring for the elderly is particularly stressful and difficult for informal caregivers. Accordingly, automated systems to assist informal caregivers will fill a great need. In this paper, a system prototype is developed to provide recommendations for elderly care to informal caregivers applying case-based reasoning (CBR) techniques....
In the growing era of technology, concentration is on the analysis of large amount of structured and unstructured data. The processing applications are inadequate to deal with these data are termed as BigData since in large amounts. In this work, an initial stage for analysing medical informatics using R-studio by R programming is attempted by two algorithms. The biomedical data is used because they...
Medical and health data are collected and stored in various document types and databases including clinical treatment records, medical examinations, prognosis health information, health billing and claims, health surveys, and community health settings. Such huge amount, wide range, and unstructured dataset characteristics imply a big challenge for researchers and government officers to analyze and...
The amount of biomedical textual information available in the web becomes more and more. It is very difficult to extract the right information that users are interested in considering the size of documents in the biomedical literatures and databases. It is nearly impossible for human to process all these data and it is even difficult for computers to extract the information since it is not stored...
Diagnosing liver disease is the challenging task for many public health physicians. In this study, we propose the framework to diagnose the hepatitis disease. For this study the adaptive rule based induction were formulated and the adaptive rule implemented in combined Robust BoxCox Transformation (RBCT) and Neural Network (NN) methods. The performance of proposed model is compared and results are...
Kidney disease is become a popular disease in around the world. The prediction of kidney disease is highly complex task while handling huge dataset. The kidney disease dataset contain patients information such as age, blood Pressure levels, albumin, sugar, counts of red blood cells etc., in the dataset there may be some missing values in some features that values may be important to predict kidney...
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