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- Citation
- Abstract
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ABSTRACT: Chromosomes are essential genomic information carriers. The identification of chromosome abnormalities is an essential part of diagnosis and treatment of genetic disorders such as chromosomal syndromes and many types of cancer. Currently available cytogenetic imaging software is designed to classify only normal chromosomes. The automation of chromosome analysis is involving segmentation of chromosomes and classification into 24 groups. Segmentation of the overlapped chromosomes is a major step toward the realization of homolog classification. Resolving chromosome overlaps is an unsolved problem in automated chromosome analysis. Current systems for automatic chromosome classification are mostly interactive and require human intervention. In this paper, an automatic procedure is proposed to obtain the separated chromosomes. The separations of overlapped and touching chromosomes are obtained by finding the intersecting (concave and convex) points with the help of Novel algorithm. The intersecting points are located on contour of the image and then the curvature function is used to find out concave points. Then the possible separation lines are plotted by using all concave points and finally construct the hypotheses for possible separation lines between concave points. The segmentation is carried out by means of a curvature function scheme, which proved to be successful.
Keywords: automatic chromosome classification, diagnosis, genetic disorders, hypothesis, interesting points.
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| Paper Type | : | Research Paper |
| Title | : | Realization of FPGA based numerically Controlled Oscillator |
| Country | : | India |
| Authors | : | Gopal D. Ghiwala, Pinakin P. Thaker, Gireeja D.Amin |
| : | 10.9790/4200-0150711 ![]() |
Keywords: Numerically Controlled Oscillator, FPGA, Look-up table, Register
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ABSTRACT: 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 the assessment of heart event-risk factors targeting in the reduction of CHD events using Weighted Association Rule Mining. The risk factors investigated were: 1) before the event: a) nonmodifiable—age, sex, and family history for premature CHD, b) modifiable—smoking before the event, history of hypertension, and history of diabetes; and 2) after the event: modifiable—smoking after the event, systolic blood pressure, diastolic blood pressure, total cholesterol, highdensity lipoprotein, low-density lipoprotein, triglycerides, and glucose. The events investigated were: myocardial infarction (MI), percutaneous coronary intervention (PCI), and coronary artery bypass graft surgery (CABGData-mining analysis was carried out using the Weighted Association Rule Mining for the afore mentioned three events using five different splitting criteria.
Keywords: Coronary heart disease (CHD), data mining, weighted association rule mining,MI,PCI
heartstats.org/datapage.asp?id=7683
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