International Journal of Research in Engineering, Science and Management Volume 4, Issue 6, June 2021 https://www.ijresm.com | ISSN (Online): 2581-5792 *Corresponding author: nadir@uob.edu.om 24 Abstract: Autonomic computing systems are similar to those in the autonomic nervous system of the human body. Autonomic computing is a system that can manage itself. This research discussed a problem, which is diagnosis of one of the most common diseases today, which is cancer. People can diagnose this disease through doctors but they can also have made a self-diagnosis for this disease without needed any doctors when they are in their home or anywhere, so they can save their time and also reducing the cost. We used an algorithm to self-diagnosis of cancer, which is case base reasoning. Case base reasoning is an automated reasoning and decision-making process whereby we solved new problems through the experiences we had accumulated in solving previous ones. So from Previous results we can self-diagnosis of cancer. Keywords: autonomic computing, case base reasoning, cancer. 1. Introduction Autonomic computing is a system that can manage itself by self-configuration, self-healing, self-optimizing and self- protection. Paul Horn, senior vice president of research for IBM, coined the term autonomic computing in 2001[1], [2]. According to Horn, the industry’s focus on creating smaller, less expensive, and more powerful systems was fueling. Autonomic computing systems are work like the human body's autonomic nervous system. An autonomic computing system would control the functioning of computer applications and systems without user, in the same way that the autonomic nervous input from the system regulates body systems without conscious input individual [3], [4]. Autonomic computing systems are exclusion of any human involvement. In fact, meaning the one of an administrator, from a rather demanding and time-consuming task of a computer stymieing operation and maintenance, it being able to function without having to be overseeing. Such a system is then expected to self-manage, thus providing the end users with uninterrupted peak performance [5]. In other words, the system should observe the internal and external conditions, as well as software and hardware issues, and lake actions to address them properly [6], [7]. This may include, for example, the process of obtaining software updates, installing them, reconfiguring if necessary, running tests, and, potentially, reverting the previous software version as it may turn out inevitable and necessary in the case of errors [8], [9]. Most precisely, such functionality may be achieving with the following four key characteristic components of the concept of self-management, i.e. self-configuration, self-optimization, self-healing, and self-protection as depicted in figure 1. Fig. 1. Autonomic computing systems The important of autonomic computing is to create computing systems capable of managing themselves largely than they do today. With the nature of autonomy, reactivity, sociality and pro-activity, software agents are promising to make autonomic computing system a reality. The inexperience staff need the guidance from the experience staff to improve their diagnostic handling skills. We have a lot of contributions that we got: 1. A survey was conducted on the trends and developments of recent CBR medical systems. 2. A case-based reasoning system is developed to demonstrate that diabetes mellitus can only be diagnosed manually beforehand. 3. How an algorithm that matches similarities improves system performance. 4. Reduce the time taken to reach a decision especially in an emergency case. The rest of the paper is structured as follows: Section 2 discusses the related work. Section 3 presents technique for proposed solution. Section 4 represents the solution model and case study. Section 5 demonstrates the analysis of result gained from experiments and section 6 include the conclusion and future work. 2. Related Work We have studied the diagnosis of engineering systems, Self-Diagnosis of Cancer Using Case Base Reasoning Algorithm Nadir Kamal Salih * Department of Computer and Electrical Engineering, University of Buraimi, AL Buraimi, Oman