Predictive Model for Likelihood of Detecting Chronic Kidney Failure and Disease Using Fuzzy Logic

Fuzzy logic is highly appropriate and valid basis for developing knowledge-based systems in medicine for different tasks and it has been known to produce highly accurate results. Examples of such tasks include syndrome differentiation, likelihood survival for sickle cell anaemia among paediatric patients, diagnosis and optimal selection of medical treatments and real time monitoring of patients. For this paper, a Fuzzy logic-based system is untaken used to provide a comprehensive simulation of a prediction model for determining the likelihood of detecting Chronic Kidney failure/diseases in humans. The Fuzzy-based system uses a 4-tuple record comprising of the following test taken: Blood Urea Test, Urea Clearance Test, Creatinine Clearance test and Estimated Glomerular Filtrate rate (eGFR). Understanding of the test was elicited from a private hospital in Ibadan through the help of an experienced and qualified nurse which also follows same test according to National Kidney Foundation. This knowledge was then used in the developing the simulated and rule-base prediction model using MATLAB software. The paper also follows the 3 major stages of Fuzzy logic. The results of fuzzification of variables, inference, model testing and defuzzification of variables was also presented. This in turn simplifies the complication involved in detecting Chronic Kidney failure/disease using Fuzzy logic based model. Keywords: Fuzzy logic, prediction model, likelihood, chronic kidney disease/failure DOI: 10.7176/JIEA/9-3-04 Publication date:May 31st 201

A MOBILE EXPERT SYSTEM APPLICATION FOR SOLVING PERSONAL COMPUTER PROBLEMS

A MOBILE EXPERT SYSTEM APPLICATION FOR SOLVING PERSONAL COMPUTER PROBLEMSAbstractFor the time being, the smartphone is the most popular device in the world a device that is still in development. Today everyone has a personal smartphone device. The capability of these smartphones is to run a variety of all kinds of applications, make user’s use it most of the time as well as for their daily tasks. The aim of this study is to develop an expert system running on android smartphones in order to solve computer problems. This approach is an accurate method to provide solution to computer problems. Design and implementing this expert system is to detect problem by asking users question and offers solution depending on user’s answer. The output solution will provide description with images to be clearer for users to understand what their issue in fact is.Keywords: Expert Systems, Mobile Application, Rule Based Systems. KİŞİSEL BİLGİSAYAR PROBLEMLERİNİN ÇÖZÜMÜ İÇİN BİR MOBİL UZMAN SİSTEM UYGULAMASIÖzetŞu anda, hala geliştirilmekte olan akıllı telefonlar dünyadaki en popüler cihazlardır. Bugün herkes kişisel bir akıllı cihaza sahiptir. Bu akıllı telefonların, kullanıcıların zamanlarının büyük bir kısmında hatta gündelik işlerinde kullandıkları çok çeşitli uygulamalar çalıştırma kabiliyetleri vardır. Bu çalışmanın amacı bilgisayar problemlerini çözmek için android akıllı telefon üzerinde çalışan bir uzman sistem geliştirmektir. Bu yaklaşım bilgisayar problemlerine çözüm sağlamak için doğru bir yöntemdir. Bu uzman sistemin tasarım ve gerçekleştirilmesi, kullanıcılara sorular sormak suretiyle problemleri tespit etmek ve kullanıcı kullanıcıların cevaplarına dayalı çözümler sunulması biçimindedir. Çıktıyı oluşturan çözüm, kullanıcılar için problemin aslında ne olduğunun anlaşılmasını sağlayan şekilli tanımlayıcı bilgiler sağlayacaktır.Anahtar Kelimeler: Uzman Sistemler, Mobil Uygulama, Kural Tabanlı Sistemler

Foundations of a smart toy development for the early detection of motoric impairments at childhood

Introduction: Monitoring of neurodevelopment from birth until the age of six aims to enhance children's abilities and autonomy. Early detection of motoric impairments at childhood can facilitate necessary diagnosis and/or treatment. Ambient Intelligence (AmI) technologies could support future application domains like motoric impairments' detection at the home environment. Objective: The creation of adequate smart monitoring solutions at home can provide professionals with reliable information about the health status of a child. Furthermore, toys and playing are crucial for the overall development of a human being. Hence, the aim of this research is to improve the exactitude of traditional evaluation methods by embedding sensors into daily life toys that provide professionals with added value supplementary evidence enhanced by Decision Support Systems (DSS). It will be possible to detect potential motoric disorders in a standard child's development that might keep undetected by traditional ways. Materials and methods: A smart toy was designed by a trans-disciplinary team of professionals under a research consortium of Madrid universities supported by EDUCERE project. The main target of this nationally funded project is to create and evaluate innovative solutions to early detect neurodevelopment disorders and trigger requested actions of early intervention. This paper focuses on the "Smart Cube", an evolution of the traditional building blocks toy. Results: The research led to validate a scalable methodology to push the creation of innovative smart toys for early prevention of disabilities. The implementation of a web based Decision Support System (DSS) allows to support the reasoning procedures required by the smart toy solution. Ongoing validation data paves the way for long scale field trials to be performed at 3 nursery schools. Conclusion: The methodology allows the interaction between a trans-disciplinary team of professionals in order to undertaken the smart toys design and construction. Furthermore, toys verification stage needs to be measured in order to adjust diagnostic and therapeutic actions to pediatric patients

Genetic Algorithm Based for Identification of Heart Disease Risk Factors

The purpose of this thesis was to examine heart disease Angina risk factors. In particular, this Thesis was organized around the central theme of adiposity, which is a prevalent Complication following SCI. Study focused on understanding the relationships between activities of daily living (ADL) and risk factors including central adiposity, lipoproteins, and triglycerides. Using genetic algorithm, while controlling for pertinent covariates such as sex, age, and leisure time physical activity (LTPA), it was found that Mobility ADL (wheeling and transferring) were negatively associated with total and LDL-cholesterol. Study also examined whether individuals who considered themselves to be overweight subsequently had less favorable subjective well-being, and were more likely to report specific secondary complications than individuals who did not consider themselves to be overweight. In summary, the findings suggest that a) participation in specific types of ADL (i.e. Mobility ADL) are associated with a lower risk and should be further explored) elevated perceived adiposity is associated with specific secondary complications and lower subjective well-being. Overall thesis findings support the overwhelming evidence of the benefits of daily physical activity and maintaining a healthy bodyweight in the SCI population DOI: 10.17762/ijritcc2321-8169.150512

A supervised cooperative learning system for early detection of language disorders

The Quality of Life of a person may depend on early attention to his neurodevel-opment disorders in childhood. Identification of language disorders under the age of six years old can speed up required diagnosis and/or treatment processes. This paper details the enhancement of a Clinical Decision Support System (CDSS) aimed to assist pediatricians and language therapists at early identification and re-ferral of language disorders. The system helps to fine tune the Knowledge Base of Language Delays (KBLD) that was already developed and validated in clinical routine with 146 children. Medical experts supported the construction of Gades CDSS by getting scientific consensus from literature and fifteen years of regis-tered use cases of children with language disorders. The current research focuses on an innovative cooperative model that allows the evolution of the KBLD of Gades through the supervised evaluation of the CDSS learnings with experts¿ feedback. The deployment of the resulting system is being assessed under a mul-tidisciplinary team of seven experts from the fields of speech therapist, neonatol-ogy, pediatrics, and neurology

Development of a Knowledge Base for smart screening of language disorders in primary care

Monitoring of neuro-evolutive development from birth until the age of six is a decisive factor in a child's quality of life. Early detection of development disorders in early childhood can facilitate necessary diagnosis and/or treatment. Primary-care pediatricians play a key role in early detection of development alterations as they can undertake the preventive and therapeutic actions necessary in the interest of a child's optimal development. The focus of this research paper is the construction of a Knowledge Base for smart screening aimed to assist pediatricians in processes of early referral in language disorders. The proposed model provides health professionals with a decision-making tool that supports referral processes. In this way, essential diagnostic and/or therapeutic actions are triggered for a comprehensive individual development. The resulting system was developed on the basis of an analysis and verification of 21 cases of children with language disorders

Issues and Structures for Sharing Medical Knowledge among Decision-Making Systems: The 1989 Arden Homsetead Retreat

Conference PaperBiomedical Informatic

Integrated Multimedia Timeline of Medical Images and Data for Thoracic Oncology Patients

A prototype multimedia medical database has been developed to provide image and textual data for thoracic oncology patients undergoing treatment of advanced malignancies. The database integrates image data from the hospital pieture archiving and communication system with textual reports from the radiology information system, alphanumeric data contained in the hospital information system, and other electronic medical data. The database presents information in a timeline format and also contains visualization programs that permit the user to view and annotate radiographic measurements in tabular or graphic form. The database provides an efficient and intuitive display of the changing status of oncology patients. The ability to integrate, manage, and access relevant multimedia information may substantially enhance communication among distributed multidisciplinary health care providers and may ensure greater consistency and completeness of patient-related data

Deployment and validation of a smart system for screening of language disorders in primary care

Neuro-evolutive development from birth until the age of six years is a decisive factor in a child?s quality of life. Early detection of development disorders in early childhood can facilitate necessary diagnosis and/or treatment. Primary-care pediatricians play a key role in its detection as they can undertake the preventive and therapeutic actions requested to promote a child?s optimal development. However, the lack of time and little specific knowledge at primary-care avoid to applying continuous early-detection anomalies procedures. This research paper focuses on the deployment and evaluation of a smart system that enhances the screening of language disorders in primary care. Pediatricians get support to proceed with early referral of language disorders. The proposed model provides them with a decision-support tool for referral actions to trigger essential diagnostic and/or therapeutic actions for a comprehensive individual development. The research was conducted by starting from a sample of 60 cases of children with language disorders. Validation was carried out through two complementary steps: first, by including a team of seven experts from the fields of neonatology, pediatrics, neurology and language therapy, and, second, through the evaluation of 21 more previously diagnosed cases. The results obtained show that therapist positively accepted the system proposal in 18 cases (86%) and suggested system redesign for single referral to a speech therapist in three remaining cases