This study included 96 meningiomas treated between the years of 1999 and
2003 .
The age of patients was between 18-80 years ,with a mean age of 49.16 years.
Females constituted 65.6% of the patients ,while males constituted 34.4%.
Large percent o
f cases was between 4th to 6th decade of age, ( 56, 2% of all
patients).
Signs of raised intracranial pressure dominated the clinical picture
presenting in 62% of patients, while epilepsy was the only symptom in 15%
of the patients . MRI was performed in 81% of patients. The other
patients were diagnosed by CT scan.
Tumors were hemispheral in 74% of patients. The operating microscope
and ultrasonic aspirator were used in 85% of cases.15% of tumors were
removed using the classical methods,
Total removal was achieved in 90% of cases. Clinical improvement was seen
in 60.45 of cases while deterioration was seen in only 5.2% of cases.
Complications included cerebral edema in five patients, and tumor
recurrence in 5.2% of cases. Tumors were benign in 88%.Mortality was
2%.
Epilepsy is a chronic neurological disorder that occurs in the brain،
and affects approximately 2% of people around the world، where
epilepsy patients face a lot of difficulties in everyday life due to the
occurrence of seizures. Electroencephalog
ram (EEG) is used in
the automated detection of epileptic seizures، which has
Characteristics of non-linear and non-stationary. In this research،
we conducted automated detection of the seizures from the scalp
EEG signals using a Level 5 Discrete Wavelet Transforms DWT to
analyze the signal and extracting statistical features (maximum،
minimum، mean، average ، standard deviation، the ratio between
the mean values) and Categorizing using artificial neural networks
ANN for classification. The suggested detection method has
89.85% detection accuracy with 90.60% sensitivity ، and 89.1%
specificity.