4 articles for “Alaa M. Elsayad”

Also matching:2 authors

Research ArticleOpen accessIn the author namesDiagnosis of Hepatitis Disease with Logistic Regression and Artificial Neural NetworksAlaa M. Elsayad, Ahmed M. Nassef, Mujahed Al-DhaifallahHepatitis C refers to the inflammatory state of the liver caused by viruses, bacteria, fungi, and exposure to toxins such as alcohol and self-immunity. The diagnosis requires investigating many laboratory tests and comparing the results to those of the former patients with the same conditions. This study presents the results of our experiments to build a hybrid system that combines … …Journal of Computer Science, Vol. 16, Issue 3 · 27 Mar 2020 · 7,470 accessesView PDF Cite

Research ArticleOpen accessIn the author namesDiagnosis of Cardiovascular Diseases with Bayesian ClassifiersAlaa Elsayad, Mahmoud FakhrCardiovascular disease or atherosclerosis is any disease affecting the cardiovascular system. They include coronary heart disease, raised blood pressure, cerebrovascular disease, peripheral artery disease, rheumatic heart disease, congenital heart disease and heart failure. They are treated by cardiologists, thoracic surgeons, vascular surgeons, neurologists and interventional radiologists. The diagnosis is an important yet complicated task that needs to be done accurately … …Journal of Computer Science, Vol. 11, Issue 2 · 25 Mar 2015 · 7,503 accessesView PDF Cite

Research ArticleOpen accessIn the author namesSteel Plates Faults Diagnosis with Data Mining ModelsMahmoud Fakhr, Alaa M. ElsayadProblem statement: Over the last two decades, Fault Diagnosis (FD) has a major importance to enhance the quality of manufacturing and to lessen the cost of product testing. Actually, quick and correct FD system helps to keep away from product quality problems and facilitates precautionary maintenance. FD may be considered as a pattern recognition problem. It has been gaining more … …Journal of Computer Science, Vol. 8, Issue 4 · 31 Jan 2012 · 11,383 accessesView PDF Cite

Research ArticleOpen accessIn the author namesPredicting the Severity of Breast Masses with Ensemble of Bayesian ClassifiersAlaa M. ElsayadProblem statement: This study evaluated two different Bayesian classifiers; tree augmented Naive Bayes and Markov blanket estimation networks in order to build an ensemble model for prediction the severity of breast masses. The objective of the proposed algorithm was to help physicians in their decisions to perform a breast biopsy on a suspicious lesion seen in a mammogram image or … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,306 accessesView PDF Cite