Expert System to assist the diagnosis of Tropical Diseases (Hospital Provincial of Cabinda) - Matumueni, Humberto Cuteso (2018)
Expert systems are computer tools based on solid methods and artificial intelligence arguments. Systems provide an explanation for solving complex problems and are only possible if the user has specific knowledge about the nature of the problem. The construction of expert systems is quite complex because it involves costs and time. The expert system developed in this thesis aims to assist physician in the diagnosis of tropical diseases and answer the question "How to assist the physician in the process of rapid diagnosis of tropical diseases and in the decision making of patients in the Hospital Provincial of Cabinda?” The objective is to develop an expert system to assist the physician in diagnosing the most common tropical diseases, such as simple malaria, cerebral malaria, typhoid and tuberculosis, are diseases with a high mortality rate in Angola in general and Cabinda in particular. For example, malaria is one of the major tropical parasitic diseases, with an incidence of more than 500 million cases per year worldwide. The expert system can be useful for saving lives. The province of Cabinda was chosen as a study area for the application of this prototype. A prototype developed using artificial intelligence techniques to help the physician diagnose the disease from a series of questions and answers. An expert system has been developed in the field of artificial intelligence to help physicians rapidly diagnose patient symptoms and signs without requiring a supplemental check or laboratory examination but only with selected symptoms and signs. It is a system of interaction with the user, who created a special attention to the creation of a very accessible interface to be accepted by people without computer skills. The system is not subject to medical notification or to a cumulative notification by physicians to administer medications to each patient remaining unchanged. Based mostly on human memory because so far there is no other way of how to provide appropriate information or the different problems encountered by a physician at all. The system also has a module explaining how, why and why not, and the concepts are presented whenever possible. It is important to recognize the collaboration that exists between the knowledge engineer and the human expert in several areas of knowledge.Despite the delay and effort to capture experiences and code in a computer program. Collaboration with the specialist was crucial to the success of this expert system. To this end, the human expert provided an extensive bibliography. The development of this system followed four phases. Phase I: was to solve the patient's problem using the conventional way without the help of the expert system. Phase II involved translating the patient's problem into standardized rules or statements and including an interface with experienced systems. Phase III: the contributions of the experts began to be translated in a computational language. Phase IV: the complete use of the system has started. The work was developed in 3 stages. In the first one, the data on tropical diseases, each with its symptoms, were collected from the professionals of the Provincial Hospital of Cabinda (Physicians and Nurses) through a questionnaire and debates. In the second, the artificial intelligence technique was used to construct the system, with a knowledgebased reasoning, an inference mechanism with two modes of reasoning back and forth. We used the Exsys Corvid tool, which is a library composed of eleven components that allowed the importation of basic knowledge and the realization of the inference process used as an alternative in the definition of production rules that formed the knowledge base of this application. In order to simplify and harmonize the points of view of the experts, decision tables, consisting of conditions and actions, have been used and the conditions or set of conditions can be met to take a series of actions. And in the third, tests were performed with physicians and patients, which allowed obtaining results to verify and validate the system with Cohen's Kappa and draw great conclusions. In summary, the different results obtained in the implementation of the expert system with a sample of 296 patients in the Cabinda Provincial Hospital show the K value, moderate in simple malaria (k = 0.54), excellent in cerebral malaria (k = 0, 87), mean in typhoid and tuberculosis (K = 0.39 and 0.28). The system validation criteria presented a good diagnostic index (k = 0.81-1.0) for moderate to severe malaria (k = 0.41-0.60) for simple and medium malaria (k = 0.21 -0.40) for typhoid fever and tuberculosis.These results are promising for the development of an expert system that assists physicians in the diagnosis of tropical diseases. The diagnostic adjustment levels provided by the system with the patients tested represented 73% of the sensitivity to tuberculosis, 69% of typhoid fever, 94% of cerebral malaria and 77% of simple malaria, favouring a tendency of 78% sensitivity. Thus, the developed system is valid, can be applied to improve the levels of assistance to physicians of the Cabinda Provincial Hospital in the diagnosis of tropical diseases that have victimized many people and can also be considered as a tool for future perspectives of development of other systems of decision support in the process of continuous improvement of health services in Cabinda.