الفهرس 
Chapter 1 IntroductionOnly 14 pages are availabe for public view
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Abstract
Due to the tremendous development in computer science, such as the development in databases, algorithms, many technologies, in this thesis the applications of artificial intelligence in biomedical informatics were used where we made some comparisons with some of the algorithms used that link artificial intelligence, biomedical informatics. The thesis summary includes biomedical data management in biomedical systems. Then perform DNA sequencing analysis to predict then predict diseases. where high-accuracy methods for machine learning have been introduced in the medical field such as K-Nearest-Neighbor (KNN), Gaussian Process Classifier (GP), Decision Tree (DT) classifier, Random Forest (RF) Classifier, Multilayer Classifier (MLP), Ada Boost Classifier, Support Vector Machine (SVM), Deep Learning (DL). In this thesis, we apply these methods to the DNA of a standard data set. The thesis proposes a biomedical data management framework based on a hybrid Bag-of-Words (BoW)+Random Forest (RF) model, which achieved 100% accuracy compared to other methods. Moreover, the data warehouse was dealt with and a classification was made for this data, where the classification was made on the basis of certain conditions in terms of the similarity between the new patient, the old patients so that the target data can be extracted where the proposed method can be used in recommending the necessary treatment protocol based on acid The algorithm was modified using the alignment , similarity matrix between nucleic acids, where the algorithm was modified based on the placement of GAP after the three hydrogen bonds, , the average accuracy was 96.5%. This thesis consists of five chapters that depend on each other. These chapters are as follows : 1- Chapter One : It consists of the introduction, some terms definitions have been explained through which the idea of this thesis was inspired, the idea of the system to be applied has been explained. 2- Chapter Two : In this chapter, previous works in the field of artificial intelligence, medical informatics also bioinformatics were clarified. 3- Chapter Three: It consists of explaining the way the platform works for the proposed system from the methods used in artificial intelligence, dealing with data ware mania to extract data, developing the algorithm used to make comparisons between DNA in addition to then specifying the treatment protocol for patients. 4- The results used, comparing them with ready-made tools already used, making statistics for the extracted results. 5- Chapter Five : It consists of what has been extracted from the works that have been implemented the consequences. In addition, future business.