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Kim, Hyunjo
Journal of Medical Biomedical and Applied Sciences
Biochemistry, Genetics & Molecular Biology Medicine & Pharmacology

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Classification Algorithms For Predicting The Risk of Osteoporotic Fracture Kim, Hyunjo
Journal of Medical Biomedical and Applied Sciences Vol 6 No 8 (2018)
Publisher : Journal of Medical Biomedical and Applied Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (661.284 KB) | DOI: 10.15520/jmbas.v6i8.133

Abstract

The information technology may provide alternative approaches to Osteoporosis disease diagnosis. This systematicreview was performed to compare the diagnostic accuracy of vertebral fracture assessment. In this study, we examinethe potential use of classification techniques on a massive volume of healthcare data, particularly in prediction ofpatients that may have Osteoporosis through its risk factors. For this purpose, we propose to develop a new solutionapproach based on Random Forest decision tree to identify the osteoporosis cases. There has been no researchin using the afore-mentioned algorithm for Osteoporosis patients‘ prediction. The reduction of the attributes consiststo enumerate dynamically the optimal subsets of the reduced attributes of high interest by reducing the degree ofcomplexity. A computer-aided system is developed for this purpose. The performance of the proposed model in thisstudy is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.
Bioinformatics Technology In Clinical And Public Health Microbiology Applying Computational Methods Kim, Hyunjo
Journal of Medical Biomedical and Applied Sciences Vol 6 No 9 (2018)
Publisher : Journal of Medical Biomedical and Applied Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2117.137 KB) | DOI: 10.15520/jmbas.v6i9.148

Abstract

The role of clinical genomics in infectious disease diagnostics and public health microbiology is the topic of discussion during a recent decade. Although much of this work is aimed at describing the structure of outbreak communities, the methodology works equally well to identify pathogens in clinical samples. Clinical genomics is the exploitation of genome sequence data for diagnostic, therapeutic, and public health purposes. Central to this field is the high-throughput DNA sequencing of genomes and metagenomes. The key concept in using clinical genomics methodology is that detection of microbes is independent of culture and is not limited to targets used for in-depth PCR assays. Rather, it is a process of generating large-scale sequence data sets that adequately sample a specimen for microbial content and then of applying computational methods to resolve the sequences into individual species, genes, pathways, or other features.
Bioinformatics Tools In Clinical Microbiology and Infectious Disease Prevention Algorithms Kim, Hyunjo
Journal of Medical Biomedical and Applied Sciences Vol 6 No 9 (2018)
Publisher : Journal of Medical Biomedical and Applied Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2246.715 KB) | DOI: 10.15520/jmbas.v6i9.157

Abstract

Bioinformatics resource is the exploitation of genome sequence data for diagnostic, therapeutic, and preventionpurposes. The role of clinical genomics in infectious disease is aimed at describing the structure of outbreakcommunities, the methodology works equally well to identify pathogens in clinical samples. Furthermore, early detectionof infectious disease in outbreaks is one of the significant issues in syndromic surveillance systems. The key concept inusing clinical genomics methodology is a process of generating large-scale sequence data sets that adequately samplea specimen for microbial content and then of applying computational methods to resolve the sequences into individualspecies, genes, pathways, or other features. It helps to provide a rapid epidemiological response and reduce morbidityand mortality. Therefore, bioinformatics model algorithms for virus transmission and prevention in terms of resistomewould be taken into consideration. The relevant future study of resistome reveals strategies that can be applied in newantibiotic discoveries.
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