Multimodal optical diagnostics of the microhaemodynamics in upper and lower limbs

The introduction of optical non-invasive diagnostic methods into clinical practice can substantially advance in the detection of early microcirculatory disorders in patients with different diseases. This paper is devoted to the development and application of the optical non-invasive diagnostic approach for the detection and evaluation of the severity of microcirculatory and metabolic disorders in rheumatic diseases and diabetes mellitus. The proposed methods include the joint use of laser Doppler flowmetry, absorption spectroscopy and fluorescence spectroscopy in combination with functional tests. This technique showed the high diagnostic importance for the detection of disturbances in peripheral microhaemodynamics. These methods have been successfully tested as additional diagnostic techniques in the field of rheumatology and endocrinology. The sensitivity and specificity of the proposed diagnostic procedures have been evaluated.<br/

Development of decision support system for the diagnosis of arthritis pain for rheumatic fever patients: Based on the fuzzy approach

Developing a Decision Support System (DSS) for Rheumatic Fever (RF) is complex due to the levels of vagueness, complexity and uncertainty management involved, especially when the same arthritis symptoms can indicate multiple diseases. It is this inability to describe observed symptoms precisely that necessitates our approach to developing a Decision Support System (DSS) for diagnosing arthritis pain for RF patients using fuzzy logic. In this paper we describe how fuzzy logic could be applied to the development of a DSS application that could be used for diagnosing arthritis pain (arthritis pain for rheumatic fever patients only) in four different stages, namely: Fairly Mild, Mild, Moderate and Severe. Our approach employs a knowledge-base that was built using WHO guidelines for diagnosing RF, specialist guidelines from Nepal and a Matlab fuzzy tool box as components to the system development. Mixed membership functions (Triangular and Trapezoidal) are applied for fuzzification and Mamdani-type is used for the fuzzy reasoning process. Input and output parameters are defined based on the fuzzy set rules

Onion RBS for Disorders Diagnosis and Treatment

Abstract: This research included the design of an initial expert system which helps farmers and specialists to diagnose and provide appropriate advice on onion plant diseases; furthermore, the management of knowledge used in the expert system was discussed. One of the key elements of this research was to find the appropriate language to diagnose the onion disease and the current situation in the knowledge base. Expert systems to be able to effectively implement the consultation, production rules were used to capture knowledge. The expert system was developed using CLIPS with the Delphi language interface. The expert system has produced good results in the analysis of onion disease cases that have been tested and enable the system to determine the correct diagnosis in all cases

Diagnosing Ankle Diseases Expert System

In recent years, technology has evolved significantly to intervene in the treatment of diseases through diagnosis online before going to the specialist doctor, where it become possible for the patient to know the name of his illness, the specialist doctor who can treat him and the multiple treatment methods through specially designed systems called expert systems. The expert system is based on the principle of asking the user gradual questions about the symptoms he feels, leading him to the result of diagnosing the illness, dealing with it quickly, and tips for permanent treatment. These systems may also help both trainee physicians and physiotherapists. This research paper is a living example of these effective applications, explaining in a simplified manner some of ankle diseases, how to deal with them and methods of physical therapy. The ankle is a small region in the leg. It is two joints, the first consist of three bones (tibia, fibula and talus underneath) which is called true ankle joint. The other is called subtalar joint have two bones: talus on top and calcaneus on the bottom. This tarsus between the end of the leg and the start of the foot facilitates the movement up-down and left-right with no problems in normal case, although, it needs a special case as Physiotherapist when gets injury. We have identified seven ankle diseases: Ankle Sprain, Fracture (of Fibula), Rheumatoid Arthritis, Rheumatoid Fever, Gout, and Osteoarthritis (Degenerative Joint) using SL5 Object Expert System Language in the work of the expert system

Intelligent technologies for real-time monitoring and decision support systems

MPhilAutomation of data processing and control of operations involving intelligent technologies that is considered the next generation technology requires error-free data capture systems in both clinical research and healthcare. The presented research constitutes a step in the development of intelligent technologies in healthcare. The proposed improvement is by automation that includes the elements of intelligence and prediction. In particular automatic data acquisition systems for several devices are developed including pervasive computing technologies for mobility. The key feature of the system is the minimisation/near eradication of erroneous data input along with a number of other security measures ensuring completeness, accuracy and reliability of the patients‟ data. The development is based on utilising existing devices to keep the cost of Data Acquisition Systems down. However, with existing technology and devices one can be limited to features required to perform more refined analysis. Research of existing and development of a new device for assessment of neurological diseases, such as MS (Multiple Sclerosis) using Stroop test is performed. The software can also be customized for use in other diseases affecting Central Nervous System such as Parkinson‟s disease. The introduction of intelligent functions into the majority of operations enables quality checks and provides on-line user assistance. It could become a key tool in the first step of patient diagnosis before referring to more advanced tests for further investigation. Although the software cannot fully ensure the diagnosis of MS or PD but can make significant contribution in the process of diagnosis and monitorin

Automated evaluation of autoantibodies on human epithelial-2 cells as an approach to standardize cell-based immunofluorescence tests

INTRODUCTION: Analysis of autoantibodies (AAB) by indirect immunofluorescence (IIF) is a basic tool for the serological diagnosis of systemic rheumatic disorders. Automation of autoantibody IIF reading including pattern recognition may improve intra- and inter-laboratory variability and meet the demand for cost-effective assessment of large numbers of samples. Comparing automated and visual interpretation, the usefulness for routine laboratory diagnostics was investigated. METHODS: Autoantibody detection by IIF on human epithelial-2 (HEp-2) cells was conducted in a total of 1222 consecutive sera of patients with suspected systemic rheumatic diseases from a university routine laboratory (n = 924) and a private referral laboratory (n = 298). IIF results from routine diagnostics were compared with a novel automated interpretation system. RESULTS: Both diagnostic procedures showed a very good agreement in detecting AAB (kappa = 0.828) and differentiating respective immunofluorescence patterns. Only 98 (8.0%) of 1222 sera demonstrated discrepant results in the differentiation of positive from negative samples. The contingency coefficients of chi-square statistics were 0.646 for the university laboratory cohort with an agreement of 93.0% and 0.695 for the private laboratory cohort with an agreement of 90.6%, P < 0.0001, respectively. Comparing immunofluorescence patterns, 111 (15.3%) sera yielded differing results. CONCLUSIONS: Automated assessment of AAB by IIF on HEp-2 cells using an automated interpretation system is a reliable and robust method for positive/negative differentiation. Employing novel mathematical algorithms, automated interpretation provides reproducible detection of specific immunofluorescence patterns on HEp-2 cells. Automated interpretation can reduce drawbacks of IIF for AAB detection in routine diagnostics providing more reliable data for clinicians

Expert System for Polymyalgia Rheumatic

Polymyalgia Rheumatica (PMR) presents with a broad spectrum of clinical manifestations and almost exclusively occurs in the population aged over 50 years. After rheumatoid arthritis, PMR is the second most common autoimmune rheumatic disorder. Visual loss is the most feared complication in temporal arteritis, and extracranial arteries. No specific laboratory parameter exists for diagnosis of PMR. Imaging techniques such as ultrasonography, MRI or F-fluorodeoxyglucose PET may be helpful in the diagnosis and evaluation of the extent of vascular involvement in these diseases. This paper presets an expert system for classification criteria for PMR, recent advances of diagnostic and therapeutic procedures. This expert System was written using SL5 Object Expert System Languag

Preceding rule induction with instance reduction methods

A new prepruning technique for rule induction is presented which applies instance reduction before rule induction. An empirical evaluation records the predictive accuracy and size of rule-sets generated from 24 datasets from the UCI Machine Learning Repository. Three instance reduction algorithms (Edited Nearest Neighbour, AllKnn and DROP5) are compared. Each one is used to reduce the size of the training set, prior to inducing a set of rules using Clark and Boswell's modification of CN2. A hybrid instance reduction algorithm (comprised of AllKnn and DROP5) is also tested. For most of the datasets, pruning the training set using ENN, AllKnn or the hybrid significantly reduces the number of rules generated by CN2, without adversely affecting the predictive performance. The hybrid achieves the highest average predictive accuracy

A review of arthritis diagnosis techniques in artificial intelligence era: Current trends and research challenges

Deep learning, a branch of artificial intelligence, has achieved unprecedented performance in several domains including medicine to assist with efficient diagnosis of diseases, prediction of disease progression and pre-screening step for physicians. Due to its significant breakthroughs, deep learning is now being used for the diagnosis of arthritis, which is a chronic disease affecting young to aged population. This paper provides a survey of recent and the most representative deep learning techniques (published between 2018 to 2020) for the diagnosis of osteoarthritis and rheumatoid arthritis. The paper also reviews traditional machine learning methods (published 2015 onward) and their application for the diagnosis of these diseases. The paper identifies open problems and research gaps. We believe that deep learning can assist general practitioners and consultants to predict the course of the disease, make treatment propositions and appraise their potential benefits

The WHF Roadmap for Reducing CV Morbidity and Mortality Through Prevention and Control of Rheumatic Heart Disease.

Rheumatic heart disease (RHD) is a preventable non-communicable condition that disproportionately affects the world's poorest and most vulnerable. The World Heart Federation Roadmap for improved RHD control is a resource designed to help a variety of stakeholders raise the profile of RHD nationally and globally, and provide a framework to guide and support the strengthening of national, regional and global RHD control efforts. The Roadmap identifies the barriers that limit access to and uptake of proven interventions for the prevention and control of RHD. It also highlights a variety of established and promising solutions that may be used to overcome these barriers. As a general guide, the Roadmap is meant to serve as the foundation for the development of tailored plans of action to improve RHD control in specific contexts