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

AbstractEbola 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 limiting factor among some participants.Second, a test was conducted among 45 people. Results from a comprehensive testing of the Ebinformatics software by allowing users to operate and use the software, revealed that 60% of them were satisfied, while 16% were not satisfied with the software, while 24% were indifferent. 69% of the users were in agreement that Ebinformatics was supportive, 20% disagreed, while 11% were indifferent. 67% found the software easy to use, 13% disagreed, while 20% were indifferent. Third, the output of the software, showing the various diagnosis and recommendations interfaces were presented. Recommendations were also given with respect to how the system can be extended, and further improved upon

Pervasive Computing in Classroom Environments and Applications

Pervasive computing is an advanced computing paradigm which makes computing available everywhere and anywhere. It allows users to interact with computers. Such computers can exist in different forms such as laptops, tablets, a pair of glasses (wearable computers) and clothes or wearable fabrics that are sensor-embedded. It is essential to explore the different applications of pervasive computing to learning in classroom environments, in order to foster learning and promote well-being among students. One of the problems currently confronting some developing countries is a lack of adequate facilities to support proper learning in classroom environments. This has had a negative impact on the performance of students at various levels of educational learning. In this paper, a review of current trends, future trends and applications of pervasive computing was explored, particularly with respect to classroom learning environments, and a generic model of pervasive computing technology was proposed for adoption in classroom learning environments of developing countries, particularly the Nigerian tertiary institution’s classroom learning environment

Android Mobile Informatics Application for some Hereditary Diseases and Disorders (AMAHD): A complementary framework for medical practitioners and patients

Hereditary diseases and disorders constitute a public health problem. Many people in rural communities of developing countries of the world are particularly ignorant about the cause, modes of transmissions and the treatment plans for such diseases. In some cases, some people lack essential knowledge between common and rare hereditary diseases.It is therefore appropriate and essential to develop a mobile application that will act as an educative resource and a good knowledge base for common and rare hereditary diseases.The aim of this research is to develop AMAHD (Android Mobile Informatics Application for some Hereditary Diseases and Disorders).The objectives of this research are to create an android mobile application that will act as a reference point and provide useful information about various hereditary diseases to medical personnel and professionals; provide additional educational resource to biological and bioinformatics researchers in different higher institutions; and provide a pedagogical, diagnostic and complementary foundational learning tool for African research students in biosciences, bioinformatics, and all other categories of students that currently engage in multidisciplinary research in the aspect of hereditary diseases.Essential data was sourced from relevant literature. We developed AMAHD through an integration of programming languages in Java and XML (Extended Markup Language). SQLite was used to implement the database. We developed a Logical Disjunction Rule-based Algorithm (LDRA) for the AMAHDâs diagnosis module.A comparative analysis between existing commercial hereditary mobile applications and AMAHD was conducted and the results presented. A world-wide online survey (spanning Africa, Asia, Europe, America and Australia) was conducted to sample the opinion of individuals across the globe on the classification of hereditary diseases as either rare or common, within their respective regions. In addition, an evaluation of AMAHD on the offline platform was conducted by administering paper questionnaires and asking users direct questions about how they respectively rate the performance of AMAHD based on certain evaluation criteria. Furthermore, a separate evaluation of AMAHD was conducted using online survey monkey. Finally, a comparative analysis between the results obtained from the online evaluation and offline evaluation of AMAHD was conducted and presented.The results of the surveymonkey online questionnaire revealed that: 58.49% of the participants agreed that AMAHD can be used to diagnose users ailments based on the hereditary disease symptoms they supplied to the mobile application; 13.21% disagreed, while 28.30% of the participants were indifferent. 71.7% of the participants agreed that AMAHD can act as a complementary resource for supplementary healthcare support; 5.66% disagreed, while 22.64% of the participants were indifferent. 88.46% of the participants agreed that AMAHD can be particularly supportive to developing countries where there is less awareness of the deadly effects on hereditary diseases; 1.92% disagreed, while 9.62% were indifferent. Finally, 86.79% of the participants agreed that AMAHD can be useful as an android health application, 13.21% disagreed. Keywords: Hereditary diseases, Android application, Medical practitioners, Informatics, Bioinformatics, Mobile informatic

Malavefes: A computational voice-enabled malaria fuzzy informatics software for correct dosage prescription of anti-malarial drugs

Malaria is one of the infectious diseases consistently inherent in many Sub-Sahara African countries. Among the issues of concern are the consequences of wrong diagnosis and dosage administration of anti-malarial drugs on sick patients; these have resulted into various degrees of complications ranging from severe headaches, stomach and body discomfort, blurred vision, dizziness, hallucinations, and in extreme cases, death. Many expert systems have been developed to support different infectious disease diagnoses, but not sure of any yet, that have been specifically designed as a voice-based application to diagnose and translate malaria patients’ symptomatic data for pre-laboratory screening and correct prescription of proper dosage of the appropriate medication. We developed Malavefes, (a malaria voice-enabled computational fuzzy expert system for correct dosage prescription of anti-malarial drugs) using Visual Basic.NET., and Java programming languages. Data collation for this research was conducted by survey from existing literature and interview from public health experts. The database for this malaria drug informatics system was implemented using Microsoft Access. The Root Sum Square (RSS) was implemented as the inference engine of Malavefes to make inferences from rules, while Centre of Gravity (CoG) was implemented as the defuzzification engine. The drug recommendation module was voice-enabled. Additional anti-malaria drug expiration validation software was developed using Java programming language. We conducted a user-evaluation of the performance and user-experience of the Malavefes software. Keywords: Informatics, Bioinformatics, Fuzzy, Anti-malaria, Voice computing, Dosage prescriptio

MAVSCOT: A fuzzy logic-based HIV diagnostic system with indigenous multi-lingual interfaces for rural Africa.

HIV still constitutes a major public health problem in Africa, where the highest incidence and prevalence of the disease can be found in many rural areas, with multiple indigenous languages being used for communication by locals. In many rural areas of the KwaZulu-Natal (KZN) in South Africa, for instance, the most widely used languages include Zulu and Xhosa, with only limited comprehension in English and Afrikaans. Health care practitioners for HIV diagnosis and treatment, often, cannot communicate efficiently with their indigenous ethnic patients. An informatics tool is urgently needed to facilitate these health care professionals for better communication with their patients during HIV diagnosis. Here, we apply fuzzy logic and speech technology and develop a fuzzy logic HIV diagnostic system with indigenous multi-lingual interfaces, named Multi-linguAl HIV indigenouS fuzzy logiC-based diagnOstic sysTem (MAVSCOT). This HIV multilingual informatics software can facilitate the diagnosis in underprivileged rural African communities. We provide examples on how MAVSCOT can be applied towards HIV diagnosis by using existing data from the literature. Compared to other similar tools, MAVSCOT can perform better due to its implementation of the fuzzy logic. We hope MAVSCOT would help health care practitioners working in indigenous communities of many African countries, to efficiently diagnose HIV and ultimately control its transmission