A new block adaptation algorithm realizing rapid identification system

2003 ◽  
Author(s):  
K. Oh'Ishi ◽  
H. Kubota ◽  
M. Onoda
Keyword(s):  
Rapid Identification ◽  
Identification System ◽  
Adaptation Algorithm

scholarly journals Reagentless Bacterial Identification Using a Combination of Multiwavelength Transmission and Angular Scattering Spectroscopy

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Debra E. Huffman ◽  
Yulia M. Serebrennikova ◽  
Jennifer M. Smith ◽  
Alison Roth ◽  
Jack N. Lindon ◽  
...  
Keyword(s):  
Bacterial Pathogens ◽  
New Technology ◽  
Rapid Identification ◽  
Clinical Isolates ◽  
Identification System ◽  
Bacterial Identification ◽  
E Coli ◽  
Chemical Reagents ◽  
Angular Scattering ◽  
Hospital Systems

Optics based technologies are being advanced by many diagnostic companies around the globe. This resurgence is being driven by several factors including novel materials, enhanced computer power, nonlinear optics, and advances in algorithmic and statistical analysis. This study expands on a previous paper that evaluated the capability of a reagent-free optical profiling platform technology that used multiwavelength transmission spectroscopy to identify bacterial pathogens from pure culture. This study combines multiwavelength angular scattering with transmission based analysis into a single algorithm that will identify bacterial pathogens. Six predominant organisms,S. aureus, E. coli,K. pneumoniaeandP. aeruginosa,E. faecalis,and coagulase negativeStaphylococcus, were analyzed from a total of 753 clinical isolates received from three large community hospital systems. The bacterial identification method used for comparison in this study was the Vitek-2 (bioMerieux) which utilizes a biochemically based identification system. All of the clinical isolates received were blinded as to their identification until completion of the optical analysis. Sensitivities ranged from 87.7 to 94.6% with specificities ranging from 97.2 to 99.9% indicating that optical profiling is a powerful and exciting new technology that could be developed for the rapid identification of pathogens without the use of chemical reagents.

Rapid Identification System of Purity and Authenticity in Cotton Varieties by SSR Markers

2017 ◽  
Vol 43 (10) ◽  
pp. 1565
Author(s):  
Xin-Yi WANG ◽  
Xian-Tao AI ◽  
Jun-Duo WANG ◽  
Ya-Jun LIANG ◽  
Zhao-Long GONG ◽  
...  
Keyword(s):  
Ssr Markers ◽  
Rapid Identification ◽  
Identification System

scholarly journals Commercial phenotypic tests (API 20E) in diagnosis of fish bacteria: a review

2008 ◽  
Vol 52 (No. 2) ◽  
pp. 49-53 ◽  
Author(s):  
N. Topic Popovic ◽  
R. Coz-Rakovac ◽  
I. Strunjak-Perovic
Keyword(s):  
Vibrio Anguillarum ◽  
Rapid Identification ◽  
Identification System ◽  
Bacterial Isolates ◽  
Yersinia Ruckeri ◽  
Fish Health ◽  
Fish Pathogens ◽  
Phenotypic Tests ◽  
Fish Bacteria ◽  
Important Fish

The available data concerning rapid identification of fish bacteria via commercial phenotypic tests demonstrate that there is no agreement regarding the choice of the tests. However, API 20E, an identification system for Enterobacteriaceae and other non-fastidious Gram-negative rods developed for clinical specimens, seems to be increasingly used for the identification of fish pathogens. In this review, adaptation of API 20E for fish bacterial isolates and its distinctiveness for fish bacteria was assessed. Some strains are wrongly identified because they are not included in the database of API 20E system. API 20E reactions should be compared with the diagnostic schemes based on reactions in conventional phenotypic tests. Due to their significance for fish health and impact on the aquaculture, and because of the need for their rapid identification, some important fish bacteria should be included in the API 20E system, such as <i>Yersinia ruckeri</i>, <i>Edwardsiella ictaluri</i>, <i>Vibrio anguillarum</i>.

scholarly journals Plasmodium Falciparum Identification in Thick Blood Preparations Using GLCM and Support Vector Machine (SVM)

2017 ◽  
Vol 2 (1) ◽  
pp. 12-20 ◽  
Author(s):  
Farah Zakiyah Rahmanti ◽  
Novita Kurnia Ningrum ◽  
Septian Enggar Sukmana ◽  
Prajanto Wahyu Adi
Keyword(s):  
Support Vector Machine ◽  
Plasmodium Falciparum ◽  
Research Result ◽  
Texture Feature ◽  
Rapid Identification ◽  
Blood Film ◽  
Support Vector ◽  
Identification System ◽  
Risk Of Death ◽  
Occurrence Matrix

Malaria is one of the serious diseases that require rapid handling, otherwise it can lead to death. One of the causes of malaria parasites is plasmodium falciparum which can cause severe or fatal malaria. Handling a medical late can increase the risk of death. Therefore, it takes a rapid identification system with a high percentage of accuracy to reduce the risk of death. This research aims to build an identification system of plasmodium falciparum in thick blood film using Gray Level Co-occurrence Matrix (GLCM) and Support Vector Machine (SVM). The GLCM is used to get texture feature values such as contrast, correlations, energy, and homogeneity from images. Those values is processed and as an input of classification using SVM. The research result using SVM for accuracy value of  plasmodium falciparum identification can reach 93.33%.

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