Editorial Open Access

Machine Learning 2018: Computer aided diagnosis in cloud environment based on multi agents system- Abbas M Al Bakry-University of Information Technology and Communications

Abstract

In this discourse we address answers for the issues of the low precise choice; low accessibility particularly in keeps up techniques and along these lines the versatility in online Computer Aided Diagnosis (CADs). Most CADs opened up on the web and gracefully a high significance clinical administration which build up the strength of the populace. Miscreants are to broaden the recognition of infection by lessening the bogus negative rate because of observational oversights. The online CADs face three significant issues: (1) The CADs can't analyze a few infections on the grounds that the side effects of those illnesses aren't accessible inside the information bases of this frameworks, (2) issue is that the accessibility of CADs is relies upon the online server which facilitated them. Web server may conceivable to forestall for upkeep which will infers to forestall the CADs frameworks. (3) The issue is versatility related with the expense if their administrators need to grow them to cover increasingly clinical issues. In this talk we proposed another system to take care of the above issues. The structure comprises of multi specialist’s framework to figure on the earth of the distributed computing. The structure comprises from three Sections: SaaS segments, PaaS segments and IaaS parts. Each segment has its own calculations and strategies. To assess the came about structure we make a study certain 150 people from clinical wellbeing part, understudies, masters, doctors and other. The outcomes highlighted great proportion of acknowledgment from the clients. Cloud infrastructures can offer an ideal platform where run MAS-based systems simulations, applications andreal-time running because of its large amount of processing and memory resources that can be dynamically configured for executing large agent-based software at unprecedented scale. Agents implemented in cloud systems can adapt to available virtual machines by using the basic properties of agents such as autonomy, pro-activity, negotiation and learning. Since “Clouds” are elastic, they can expand and shrink based on demand of users or applications. This property is very useful for the scalable execution of the MAS applications and simulation that are able to adapt to the available resources. In summary, agent can find in cloud computing infrastructures the appropriate platform where to run and accesslarge data. However, a major problems with this kind of medical diagnosis application which deployed and hosted by cloud computing are the need of new knowledge and data in order to get more accuracy in diagnosis decision, Because these systems are specific with space storage in the case of increase should increase the cost of storage, so they be unable to be storing all new sources in their cloud storage. In addition, these systems need to search periodically from time to time on new data sources and that will cost them increase in the use of processors and does and increasing in the cost and not guarantee a totally get to know new source. Collaborative Computer Aided Diagnosissystemshas other names like telemedicine [13] which is a way to provide health care services at a distance that is being leveraged by the evolution of informatics and telecommunications. Because the rapid advanceof Information and Communication Technology (ICT)and lowof its cost, the telemedicine scenario is being widely addressed [14-16]by many health care service providers.

Biography :

Abbas M Al Bakry has completed his PhD in Computer Science (Artificial Intelligence) from the University of Technology, Baghdad, Iraq. Currently, he is the President of the University of IT and Communications in Baghdad, General Chair of the NTICT annual conference-Baghdad, Editor in Chief of IJCI Iraqi Journal for Computers and Informatics, Editor-in-Chief, Intelligent Computing in the IJNC International Journal of Network Computing and Advanced Information Management and Editor in JCIT, AISS, JINT, IJACT, IJIIP international journals.

Abbas M Al Bakry

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