Ebinformatics: Ebola fuzzy informatics systems on the diagnosis, prediction and recommendation of appropriate treatments for Ebola virus disease (EVD)

Abstract

a b s t r a c tEbola Virus Disease (EVD) also known as the Ebola hemorrhagic fever is a very deadly infectious disease to humankind. Therefore, a safer and complementary method of diagnosis is to employ the use of an expert system in order to initiate a platform for pre-clinical treatments, thus acting as a precursor to comprehensive medical diagnosis and treatments. This work presents a design and implementation of informatics software and a knowledge-based expert system for the diagnosis, and provision of recommendations on the appropriate type of recommended treatment to the Ebola Virus Disease (EVD).In this research an Ebola fuzzy informatics system was developed for the purpose of diagnosing and providing useful recommendations to the management of the EVD in West Africa and other affected regions of the world. It also acts as a supplementary resource in providing medical advice to individuals in Ebola -ravaged countries. This aim was achieved through the following objectives: (i) gathering of facts through the conduct of a comprehensive continental survey to determine the knowledge and perception level of the public about factors responsible for the transmission of the Ebola Virus Disease (ii) develop an informatics software based on information collated from health institutions on basic diagnosis of the Ebola Virus Disease-related symptoms (iii) adopting and marrying the knowledge of fuzzy logic and expert systems in developing the informatics software. Necessary requirements were collated from the review of existing expert systems, consultation of journals and articles, and internet sources. Online survey was conducted to determine the level at which individuals are aware of the factors responsible for the transmission of the Ebola Virus Disease (EVD). The expert system developed, was designed to use fuzzy logic as its inference mechanism along with a set of rules. A knowledge base was created to help provide diagnosis on the Ebola Virus Disease (EVD). The Root Sum Square (RSS) was adopted as a fuzzy inference method. The degree of participation of each input parameter was shown using the triangular membership function and the defuzzification technique used is the Center of Gravity (CoG).The resulting software produced a user-friendly desktop-based, Windows-based, application and the tools used were explained in the results section in three (3) separate phases. First, a comprehensive online survey was conducted over a period of about 3-9 months. 100 Participants participated in the survey on the perception and knowledge analysis of different individuals about Ebola Virus Disease (EVD) transmission factors. 31% of the participants didn't know that there is presently no cure for Ebola. 28% believed that there is presently a cure for Ebola. 43% agreed that Ebola is both air-borne and water-borne, while 33% disagreed, 24% do not know. 23% believed that insects and mosquitoes can help in transmitting the Ebola Virus Disease (EVD), while 30% were completely ignorant. We noticed that ignorance was a major limiti...

Fuzzy Expert System Generalised Model for Medical Applications

“…The surveys performed by Metaxiotis and Samouilidis [23], by Patel and colleagues [12], by Mishraand and Prakash [15] and by Nath and Prasenjit [17] associated with our own survey [1], [3], [13], [14], [16], [19], [20], [26], [28] that fuzzy logic application in medicine has gone through the development stage and produced differentiated models. The finding is that all of them have the following common features: (a) symptom identification, (b) symptom fuzzy set definition (fuzzification), (c) rule base definition, (d) output defuzzification, (e) fact establishment and (f) system test.…”

“…• Test Case Presentation Using a simplified version of the medical example provided in [3] and [28], let us consider the clinical statement that someone can have Ebola Haemorrhagic Fever into three different stages, say "No Ebola", "Medium Ebola" and "Severe Ebola". Three clinical fields have been considered as an experimental sample: Body Temperature (Fever), Vomiting and Contact with a person with Ebola Haemorrhagic Fever.…”

Epidemic Alert System: A Web-based Grassroots Model

“…The researchers proposed a One Health System that is based on genomics diagnostics and epidemiology integration into existing disease surveillance systems [6]. The researchers envisioned a system that integrates human, animal and environmental health to proffer disease surveillance solutions to regions of the world with inadequate to non-existent laboratory facilities [7]. The researchers paid particular attention to how several epidemics like the Ebola and Zika progressed uninhibited for months and unnoticed by even the most advanced disease surveillance systems until they were discovered much later when they have grown to epic proportions.…”

A review on the antagonist Ebola: A prophylactic approach

“…In addition, software tools are also developed to identify EVD patients, along with the risk of EVD suffering in the future. Ebinformatics Software [32], known to be Ebola Fuzzy Informatics system, is developed in order to diagnose, prescribe appropriate medications to EVD patients. Based on the user evaluation result, this software has proven to be a valuable addition to the operational and research enterprise to fight against Ebola [32].…”

“…Ebinformatics Software [32], known to be Ebola Fuzzy Informatics system, is developed in order to diagnose, prescribe appropriate medications to EVD patients. Based on the user evaluation result, this software has proven to be a valuable addition to the operational and research enterprise to fight against Ebola [32]. This multifaceted yet single platform has been achieved by gathering information such as factors that cause Ebola-like signs and symptoms, and a system was developed based on facts for the prognosis and diagnosis of the disease.…”