An intelligent decision support tool for early diagnosis of functional pituitary adenomas

In this work, a web based integrated Medical Decision Support System (MDSS) tool for mainly early diagnosis of functional pituitary adenomas (i.e., somatotrophinoma, corticotrophinoma and prolactinoma) is developed. In the MDSS tool, hormone diseases are described by means of well-classified set of attributes generated from the typical sign and symptoms of disorders.The proposed tool is based on a stationary linear stochastic system model which specifically predicts the selected hormone diseases employing certain system parameters. The MDSS tool is user friendly which includes questions and answers at the opening session of the self-test. Questions and answers session will be completed by “yes” or “no” type of simple-responses. Based on our clinical results, MDSS tool yields more than 99% correct decisions on the selected hormone diseases. It is expected that effective use of the proposed MDSS tool will save substantial amount of valuable time of an expert endocrinologists and minimizes the cost of diagnosis. Furthermore, it will provide the opportunity for early diagnosis for the patient and the expert medical doctor to take the necessary preventive measures.Publisher's Versio

Smear plus Detect-TB for a sensitive diagnosis of pulmonary tuberculosis: a cost-effectiveness analysis in an incarcerated population

Background: Prison conditions can favor the spread of tuberculosis (TB). This study aimed to evaluate in a Brazilian prison: the performance and accuracy of smear, culture and Detect-TB; performance of smear plus culture and smear plus Detect-TB, according to different TB prevalence rates; and the cost-effectiveness of these procedures for pulmonary tuberculosis (PTB) diagnosis. Methods: This paper describes a cost-effectiveness study. A decision analytic model was developed to estimate the costs and cost-effectiveness of five routine diagnostic procedures for diagnosis of PTB using sputum specimens: a) Smear alone, b) Culture alone, c) Detect-TB alone, d) Smear plus culture and e) Smear plus Detect-TB. The cost-effectiveness ratio of costs were evaluated per correctly diagnosed TB case and all procedures costs were attributed based on the procedure costs adopted by the Brazilian Public Health System. Results: A total of 294 spontaneous sputum specimens from patients suspected of having TB were analyzed. The sensibility and specificity were calculated to be 47% and 100% for smear; 93% and 100%, for culture; 74% and 95%, for Detect-TB; 96% and 100%, for smear plus culture; and 86% and 95%, for smear plus Detect-TB. The negative and positive predictive values for smear plus Detect-TB, according to different TB prevalence rates, ranged from 83 to 99% and 48 to 96%, respectively. In a cost-effectiveness analysis, smear was both less costly and less effective than the other strategies. Culture and smear plus culture were more effective but more costly than the other strategies. Smear plus Detect-TB was the most cost-effective method. Conclusions: The Detect-TB evinced to be sensitive and effective for the PTB diagnosis when applied with smear microscopy. Diagnostic methods should be improved to increase TB case detection. To support rational decisions about the implementation of such techniques, cost-effectiveness studies are essential, including in prisons, which are known for health care assessment problems

Automatic screening and classification of diabetic retinopathy and maculopathy using fuzzy image processing

Digital retinal imaging is a challenging screening method for which effective, robust and cost-effective approaches are still to be developed. Regular screening for diabetic retinopathy and diabetic maculopathy diseases is necessary in order to identify the group at risk of visual impairment. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images by employing fuzzy image processing techniques. The paper first introduces the existing systems for diabetic retinopathy screening, with an emphasis on the maculopathy detection methods. The proposed medical decision support system consists of four parts, namely: image acquisition, image preprocessing including four retinal structures localisation, feature extraction and the classification of diabetic retinopathy and maculopathy. A combination of fuzzy image processing techniques, the Circular Hough Transform and several feature extraction methods are implemented in the proposed system. The paper also presents a novel technique for the macula region localisation in order to detect the maculopathy. In addition to the proposed detection system, the paper highlights a novel online dataset and it presents the dataset collection, the expert diagnosis process and the advantages of our online database compared to other public eye fundus image databases for diabetic retinopathy purposes

Automated Glaucoma Detection Using Hybrid Feature Extraction in Retinal Fundus Images

Glaucoma is one of the most common causes of blindness. Robust mass screening may help to extend the symptom-free life for affected patients. To realize mass screening requires a cost-effective glaucoma detection method which integrates well with digital medical and administrative processes. To address these requirements, we propose a novel low cost automated glaucoma diagnosis system based on hybrid feature extraction from digital fundus images. The paper discusses a system for the automated identification of normal and glaucoma classes using higher order spectra (HOS), trace transform (TT), and discrete wavelet transform (DWT) features. The extracted features are fed to a support vector machine (SVM) classifier with linear, polynomial order 1, 2, 3 and radial basis function (RBF) in order to select the best kernel for automated decision making. In this work, the SVM classifier, with a polynomial order 2 kernel function, was able to identify glaucoma and normal images with an accuracy of 91.67%, and sensitivity and specificity of 90% and 93.33%, respectively. Furthermore, we propose a novel integrated index called Glaucoma Risk Index (GRI) which is composed from HOS, TT, and DWT features, to diagnose the unknown class using a single feature. We hope that this GRI will aid clinicians to make a faster glaucoma diagnosis during the mass screening of normal/glaucoma images

Clinical decision modeling system

<p>Abstract</p> <p>Background</p> <p>Decision analysis techniques can be applied in complex situations involving uncertainty and the consideration of multiple objectives. Classical decision modeling techniques require elicitation of too many parameter estimates and their conditional (joint) probabilities, and have not therefore been applied to the problem of identifying high-performance, cost-effective combinations of clinical options for diagnosis or treatments where many of the objectives are unknown or even unspecified.</p> <p>Methods</p> <p>We designed a Java-based software resource, the Clinical Decision Modeling System (CDMS), to implement Naïve Decision Modeling, and provide a use case based on published performance evaluation measures of various strategies for breast and lung cancer detection. Because cost estimates for many of the newer methods are not yet available, we assume equal cost. Our use case reveals numerous potentially high-performance combinations of clinical options for the detection of breast and lung cancer.</p> <p>Results</p> <p>Naïve Decision Modeling is a highly practical applied strategy which guides investigators through the process of establishing evidence-based integrative translational clinical research priorities. CDMS is not designed for clinical decision support. Inputs include performance evaluation measures and costs of various clinical options. The software finds trees with expected emergent performance characteristics and average cost per patient that meet stated filtering criteria. Key to the utility of the software is sophisticated graphical elements, including a tree browser, a receiver-operator characteristic surface plot, and a histogram of expected average cost per patient. The analysis pinpoints the potentially most relevant pairs of clinical options ('critical pairs') for which empirical estimates of conditional dependence may be critical. The assumption of independence can be tested with retrospective studies prior to the initiation of clinical trials designed to estimate clinical impact. High-performance combinations of clinical options may exist for breast and lung cancer detection.</p> <p>Conclusion</p> <p>The software could be found useful in simplifying the objective-driven planning of complex integrative clinical studies without requiring a multi-attribute utility function, and it could lead to efficient integrative translational clinical study designs that move beyond simple pair wise competitive studies. Collaborators, who traditionally might compete to prioritize their own individual clinical options, can use the software as a common framework and guide to work together to produce increased understanding on the benefits of using alternative clinical combinations to affect strategic and cost-effective clinical workflows.</p

Towards an Effective Decision Support System for Diabetic Foot Ulcers Diagnostic and Treatment Assessment

Diabetes mellitus (DM) is a fast-growing metabolic condition that threatens human population quality of living in the overcoming decades. One of its severe consequences is diabetic foot ulcers (DFU), which affect up to a quarter of the DM patients in their lifetime. This consequence leads to high health costs and significant decrease of the patients’ quality of life and self-esteem. In order to cope with the rising demands of heath resources and shortage in clinical human assets intelligent computational tools are required to aid in the decision where a patient is in an early stage of a DFU development and on the appraisal of a DFU treatment. It is aim of this research to provide a critical overview of the existing decision support systems (DSS) and publicly available research datasets for diabetic foot ulcers early diagnosis and treatment assessment, and thus proposing a new infrastructure system to deal with it overcoming the past attempts. The existing DFU DSS failed in being introduced in clinical practice due to total discrepancy with current daily clinical practice with DFU and the publicly available DM research datasets are shorter in data for feeding a new DSS. This research presents the actual and promising future data required for effective decisions and discloses a proposed architecture for a DSS applicable to DFU early diagnosis and treatment evaluation. Implementing the proposed system will take time but it will definitely contribute to cope with the patient demands, associated cost reduction and promotion of patients care.info:eu-repo/semantics/publishedVersio

Shrinking the Malaria Map: A Prospectus on Malaria Elimination

\ud Thirty-nine countries across the world are making progress toward malaria elimination. Some are committed to nationwide elimination, while others are pursuing spatially progressive elimination within their borders. Influential donor and multilateral organizations are supporting their goals of achieving malaria-free status. With elimination back on the global agenda, countries face a myriad of questions. Should they change their programs to eliminate rather than control malaria? What tools are available? What policies need to be put into place? How will they benefit from elimination? Unfortunately, answers to these questions, and resources for agencies and country program managers considering or pursuing elimination, are scarce. The 39 eliminating countries are all positioned along the endemic margins of the disease, yet they naturally experience a variety of country characteristics and epidemiologies that make their malaria situations different from one another. The Malaria Elimination Group (MEG) and this Prospectus recognize\ud that there is no single solution, strategy, or time line that will be appropriate for every country, and each is encouraged to initiate a comprehensive evaluation of its readiness and strategy for elimination. The Prospectus is designed to guide countries in conducting these assessments. The Prospectus provides detailed and informed discussion on the practical means of achieving and sustaining zero transmission. It is designed as a road map, providing direction and options from which to choose an appropriate path. As on all maps, the destination is clearly marked, but the possible routes to reach it are numerous. The Prospectus is divided into two sections: Section 1 Eliminating Malaria comprises four chapters covering the strategic components important to the periods before, during, and after an elimination program. Section 2 Tools for the Job, comprises six chapters that outline basic information about how interventions in an elimination program will be different from those in a control setting. Chapter 1, Making the Decision, evaluates the issues that a country should consider when deciding whether or not to eliminate malaria. The chapter begins with a discussion about the quantitative and qualitative benefits that a country could expect from eliminating malaria and then recommends a thorough feasibility assessment. The feasibility assessment is based on three major components: operational, technical, and financial feasibility. Cross-border and regional collaboration is a key subject in this chapter. Chapter 2, Getting to Zero, describes changes that programs must consider when moving from sustained control to an elimination goal. The key strategic issues that must be addressed are considered, including supply chains, surveillance systems, intersectoral collaboration, political will, and legislative framework. Cross-border collaboration is again a key component in Getting to Zero. Chapter 3, Holding the Line, provides recommendations on how to conduct an assessment of two key factors that will affect preventing the reemergence of malaria once transmission is interrupted: outbreak risk and importation risk. The chapter emphasizes the need for a strong surveillance system in order to prevent and, if necessary, respond to imported cases. Chapter 4, Financing Elimination, reviews the cost-effectiveness of elimination as compared with sustained control and then presents the costs of selected elimination programs as examples. It evaluates four innovative financing mechanisms that must support elimination, emphasizing the need for predictable and stable financing. Case studies from Swaziland and two provinces in China are provided. Chapter 5, Understanding Malaria, considers malaria from the point of view of elimination and provides a concise overview of the current burden of the disease, malaria transmission, and the available interventions that can be used in an elimination program. Chapter 6, Learning from History, extracts important lessons from the Global Malaria Eradication Program and analyzes some elimination efforts that were successful and some that were unsuccessful. The chapter also reviews how the malaria map has been shrinking since 1900. xiv A Prosp ectus on Mala ria Elimi natio n\ud Chapter 7, Measuring Malaria for Elimination, provides a precise language for discussing malaria and gives the elimination discussion a quantitative structure. The chapter also describes the role of epidemiological theory and mathematical modeling in defining and updating an elimination agenda for malaria. Chapter 8, Killing the Parasite, outlines the importance of case detection and management in an elimination setting. Options for diagnosis, the hidden challenge of Plasmodium vivax in an elimination setting, and the impact of immunity are all discussed. Chapter 9, Suppressing the Vector, explores vector control, a necessary element of any malaria program. It considers optimal methods available to interrupt transmission and discusses potential changes, such as insecticide resistance, that may affect elimination efforts. Chapter 10, Identifying the Gaps — What We Need to Know, reviews the gaps in our understanding of what is required for elimination. The chapter outlines a short-term research agenda with a focus on the operational needs that countries are facing today. The Prospectus reviews the operational, technical, and financial feasibility for those working on the front lines and considers whether, when, and how to eliminate malaria. A companion document, A Guide on Malaria Elimination for Policy Makers, is provided for those countries or agencies whose responsibility is primarily to make the policy decisions on whether to pursue or support a malaria elimination strategy. The Guide is available at www.malaria eliminationgroup.org

Ethical hurdles in the prioritization of oncology care

With finite resources, healthcare payers must make difficult choices regarding spending and the ethical distribution of funds. Here, we describe some of the ethical issues surrounding inequity in healthcare in nine major European countries, using cancer care as an example. To identify relevant studies, we conducted a systematic literature search. The results of the literature review suggest that although prevention, access to early diagnosis, and radiotherapy are key factors associated with good outcomes in oncology, public and political attention often focusses on the availability of pharmacological treatments. In some countries this focus may divert funding towards cancer drugs, for example through specific cancer drugs funds, leading to reduced expenditure on other areas of cancer care, including prevention, and potentially on other diseases. In addition, as highly effective, expensive agents are developed, the use of value-based approaches may lead to unacceptable impacts on health budgets, leading to a potential need to re-evaluate current cost-effectiveness thresholds. We anticipate that the question of how to fund new therapies equitably will become even more challenging in the future, with the advent of expensive, innovative, breakthrough treatments in other therapeutic areas

An Intelligent Data Mining System to Detect Health Care Fraud

The chapter begins with an overview of the types of healthcare fraud. Next, there is a brief discussion of issues with the current fraud detection approaches. The chapter then develops information technology based approaches and illustrates how these technologies can improve current practice. Finally, there is a summary of the major findings and the implications for healthcare practice

Comparison of different classification algorithms for fault detection and fault isolation in complex systems

Due to the lack of sufficient results seen in literature, feature extraction and classification methods of hydraulic systems appears to be somewhat challenging. This paper compares the performance of three classifiers (namely linear support vector machine (SVM), distance-weighted k-nearest neighbor (WKNN), and decision tree (DT) using data from optimized and non-optimized sensor set solutions. The algorithms are trained with known data and then tested with unknown data for different scenarios characterizing faults with different degrees of severity. This investigation is based solely on a data-driven approach and relies on data sets that are taken from experiments on the fuel system. The system that is used throughout this study is a typical fuel delivery system consisting of standard components such as a filter, pump, valve, nozzle, pipes, and two tanks. Running representative tests on a fuel system are problematic because of the time, cost, and reproduction constraints involved in capturing any significant degradation. Simulating significant degradation requires running over a considerable period; this cannot be reproduced quickly and is costly