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Sequential patterns mining from data is a well stated data mining problem. It has a number of applications such as DNA sequencing, signal processing, speech analysis etc. In this problem, it is require to mine the causal relationship between different events. An event is a non-empty disordered collection of items. One of the important applications of sequential pattern mining is in medical data. Sequential...
ELearning, as an efficient and flexible method of learning, has drawn more and more attention from researchers and practitioners in the past decades. The use of ELearning system is spreading rapidly in today's learning process and it is drastically changing the field of current scenario to get the information. This article describes the framework and methods which will be exploited to disseminate...
It is known that unhealthy diet, irregular life, work pressure and other factors can result in a number of diseases. Diabetes mellitus, peptic ulcer, and gastro-enteritis are just a few examples. To reduce these diseases, diet management is becoming an indispensable part in our daily lives. The main purpose of this study is to build a diet management system that can provide the user's correct nutritional...
Nowadays, we can see an increasing number of studies in genomics that try to find out ways to detect diseases and also better prevention methods. The public would gain a lot of benefits from the studies. With the rapid development of genotyping technology, it creates opportunity to the researchers to go depth to the genetic and look into the variants. Most of the time, researchers would found different...
Data from medical imaging system need to be analysed for diagnostics and clinical purposes. In a computerized system, the analysis normally involves classification process to determine disease and its condition. In an earlier work based on a database of 315 fundus images (FINDeRS), it is found that the foveal avascular zone (FAZ) enlargement strongly correlates with diabetic retinopathy (DR) progression...
Effective patient similarity assessment is important for clinical decision support. It enables the capture of past experience as manifested in the collective longitudinal medical records of patients to help clinicians assess the likely outcomes resulting from their decisions and actions. However, it is challenging to devise a patient similarity metric that is clinically relevant and semantically sound...
Abstract-We present a novel Bayesian network (BN) to classify strains of Mycobacterium tuberculosis complex (MTBC) into six major genetic lineages using mycobacterial interspersed repetitive units (MIRUs), a high-throughput biomarker. MTBC is the causative agent of tuberculosis (TB), which remains one of the leading causes of disease and morbidity world-wide. DNA fingerprinting methods such as MIRU...
Prostate gland diseases, including cancer, are estimated to be of the leading causes of male deaths worldwide and their management are based on clinical practice guidelines regarding diagnosis and continuing care. HIROFILOS-II is a prototype hybrid intelligent system for diagnosis and treatment of all prostate diseases based on symptoms and test results from patient health records. It is in contrast...
The discovery of biomarkers and the underlying causes of diseases are enabled through the analysis of biological samples and data stored in biobanks. Biological samples and their associated data are expensive to collect and maintain, and it is important to store and manage them efficiently. During processing, samples and data go through a number of procedures and techniques, which are often in different...
Nowadays, many studies of the discovery of the relative pattern of a disease, but some of them do not consider the data privacy of patients completely, and others are not very effective to find the pattern. In this paper, we propose a novel approach to deal with the above problems. We employ intuitionistic fuzzy set, alpha-cuts, and Apriori algorithm to discovery the relative pattern of a disease...
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