Age estimation in Egyptian children: Comparison between different methods

2018 ◽  
Vol 5 (18) ◽  
pp. 1-4
Keyword(s):  
Age Estimation ◽  
Egyptian Children

Age estimation in Egyptian children by measurements of carpals and epiphyses of the ulna and radius

2014 ◽  
Vol 2 (3) ◽  
pp. 121-125 ◽  
Author(s):  
Amal A. El-Bakary ◽  
Sohayla M. Attalla ◽  
Shaza M. Hammad ◽  
Rasha A. El-Ashry ◽  
Stefano De Luca ◽  
...  
Keyword(s):  
Age Estimation ◽  
Egyptian Children

Dental age estimation in Egyptian children, comparison between two methods

2010 ◽  
Vol 17 (7) ◽  
pp. 363-367 ◽  
Author(s):  
Amal A. El-Bakary ◽  
Shaza M. Hammad ◽  
Fatma Mohammed
Keyword(s):  
Age Estimation ◽  
Dental Age ◽  
Dental Age Estimation ◽  
Egyptian Children

COMPARISION OF DENTAL SCORING SYSTEM WITH RADIOGRAPHIC SKELETAL SYSTEM IN AGE ESTIMATION

JKCD ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 9-11
Author(s):  
Sadaf Ambreen
Keyword(s):  
Age Estimation ◽  
Scoring System ◽  
Skeletal Age ◽  
Chronological Age ◽  
Age Group ◽  
Dental Age ◽  
Scoring Method ◽  
Cross Sectional ◽  
Study Results ◽  
Male Subjects

Objectives: To compare Demirjian Dental scoring method with Greulich-Pyle (GP) Skeletal method of age estimation in pubertal children. Materials and Methods: Sample of the study included 267 male healthy subjects of 11-16 years of age group.. Demirjian Scoring system was utilized to evaluate the orthopantomograms to assess their Dental age and the Hand-Wrist radiographs were analyzed to calculate the skeletal age by utilizing GP atlas. Chronological age was obtained from the date of birth of the subject .Both methods were compared with one another and with the chronological age. It was a cross-sectional study and only healthy male subjects without any clinical abnormalities were included in the study. Results: A total of 267 male subjects of 11-16 years of age group were assessed by Demirjian and Greulich Pyle Methods. Both were compared with Chronological Age. Data obtained was statistically analyzed and the Student “t” test was applied in the study population. The mean difference between Chronolgical age and dental age was 0.69years and that of chronological age and skeletal age was 0.87 years. It was observed from dental age assessment that it does not differ much from the skeletal age. Conclusion: It was concluded that Demirjian method of Age Estimation is more precise than Greulich Pyle method of Age Estimation. Furthermore both methods can be used selectively in Medicolegal cases to access bone age which can be easily correlated to chronological age.

A Review of Different Techniques of Age Estimation from Human Face

2018 ◽  
Vol 4 (10) ◽  
pp. 6
Author(s):  
Khemchandra Patel ◽  
Dr. Kamlesh Namdev
Keyword(s):  
Age Estimation ◽  
Real Life ◽  
Extraction Methods ◽  
Human Face ◽  
Age Changes ◽  
Missing Children ◽  
Different Types ◽  
Age Variation ◽  
Human Faces ◽  
Facial Age

Age changes cause major variations in the appearance of human faces. Due to many lifestyle factors, it is difficult to precisely predict how individuals may look with advancing years or how they looked with "retreating" years. This paper is a review of age variation methods and techniques, which is useful to capture wanted fugitives, finding missing children, updating employee databases, enhance powerful visual effect in film, television, gaming field. Currently there are many different methods available for age variation. Each has their own advantages and purpose. Because of its real life applications, researchers have shown great interest in automatic facial age estimation. In this paper, different age variation methods with their prospects are reviewed. This paper highlights latest methodologies and feature extraction methods used by researchers to estimate age. Different types of classifiers used in this domain have also been discussed.

Comparing the Genetic Detox Ability and Heavy Metal Burden in a Cohort of Samples of Egyptian Children and those with Autistic Spectrum Disorder

2019 ◽  
Author(s):  
Blaurock-Busch E
Keyword(s):  
Heavy Metal ◽  
Autism Spectrum ◽  
Control Group ◽  
Potentially Toxic Metals ◽  
Gstt1 Null Genotype ◽  
Egyptian Children ◽  
Glutathione S Transferases ◽  
Metal Burden ◽  
Detoxification Pathway

The heavy metal burden of patients with Autism spectrum disorders (ASD) has been widely discussed [1-5]. Present knowledge suggests that ASD patients, compared to ‘normal’s’ show a greater metal burden, which may be a cause of the ASD pathogenesis, possibly due to a limited detoxification potential. We thus aimed to evaluate if the metal burden of ASD children is due to comprised detoxification ability, and if missing of enzymes such as the glutathione-S-transferases provide an explanation, or if additional factors play a role. Genetically, we noticed a slight difference in the detoxification ability of the ASD group compared to the Control group. In the ASD group, carrier of the genotype GSTT1 null genotype (i.e. the homozygous loss) are 1.7 times more common as in the Control group and the GSTT1 allele is more frequent in the ASD patient collective. These findings are not statistically significant but indicate a trend. In addition, our data indicates that levels of potentially toxic metals in blood and hair of both groups demonstrate a similar immediate and long-term exposure. However, 36% of the ASD group showed signs of zinc deficiency compared to 11% of the Control group and this points towards inefficiency of the Phase I detoxification pathway. More research is needed to explore the role of other elements in the detoxification pathway.

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