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Register a new userتحري أمراض أكسدة الأحماض الدسمة عند حديثي الولادة باستخدام مقياس الطيف الكتلوي الترادفي
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Damascus University رسالة ماجستير
Publication date
2015
fields
Pharmacy
and research's language is
العربية
Created by
Shamra Editor
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تعتبر اضطرابات أكسدة الاحماض الدسمة مجموعة من اضطرابات الاستقلاب الوسيط الموروثة حيث تنتقل بوراثة صبغية جسدية متنحية مسببة طيفاً واسعاً من التظاهرات السريرية التي تحمل مخاطر عالية من المراضة والوفيات لدى الولدان والاطفال المصابين
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الشنار الفاهوم س تحري اضطرابات استقلاب الأحماض العضوية لدى عدد من المرضى المشتبه بإصابتهم باضطرابات الاستقلاب الوسيط في مستشفى الأطفال الجامعي في دمشقمجلة التشخيص المخبري
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مسح استقصائي لاضطرابات استقلاب الحموض الأمينية عند حديثي الولادة بواسطة مقياس الطيف الكتلوي الترادفي
A retrospective study over 3 years was conducted in NICU of Damascus
university to explain any change in the bacteriological profile of neonatal
sepsis and to prove the need to change the treatment policy. This study was
carried out on the neonate
s admitted on NICU between 1/1/02 and
31/12/2004 who had the diagnosis of sepsis. We had the results of blood
culture and the resistance report from the patients files and the archive of
our bacteriological laboratory. we compared the results with chi square.
تمتلك اخطاء الاستقلاب الخلقية بشكل عام بما فيها اضطرابات الحموض العضوية وهي الاضطرابات -موضع دراستنا - طيفاً من الاعراض مشابهاً للعديد من الأمراض الشائعة وخاصة الانتانات مما يؤدي لالتباس وتأخير التشخيص
This study was conducted in Neonatal Intensive Care Unite of Children
Hospital of Damascus University from 1/6/97 to 31/12/97. The study led to the
following results:
1485 admissions over the inducated period resulted in 790 death
cases. The mort
ality rate was 53.19%.
Masculinity, prematurity, low-birth weight and the general bad
condition at admittance are the major risk-factors.
There was no clear effect of controlled or uncontrolled pregnancy,
location of delivery and patient transport on the mortality rate.
Infectious diseases are the main cause of mortality, followed by
respiratory diseases, congenital malformation, neurologic diseases,
surgical conditions and heart diseases respectively.
Heart disease is the leading cause of death in the world over the past 10 years. Researchers have been using several data mining techniques to help health care
professionals in the diagnosis of heart disease. Decision Tree is one of the successful d
ata mining techniques used. However, most research has applied J4.8 Decision Tree, based on Gain Ratio and binary discretization. Gini Index
and Information Gain are two other successful types of Decision Trees that are less used in the diagnosis of heart disease. Also other discretization techniques, voting method, and reduced error pruning are known to produce
more accurate Decision Trees. This research investigates applying a range of techniques to different types of Decision Trees seeking better performance in heart disease diagnosis. A widely used benchmark data set is
used in this research. To evaluate the performance of the alternative Decision Trees the sensitivity, specificity, and accuracy are calculated. The research proposes a model that outperforms J4.8 Decision Tree and Bagging algorithm in the diagnosis of heart disease patients.
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