The Experts below are selected from a list of 5601 Experts worldwide ranked by ideXlab platform
Huiju Tsai - One of the best experts on this subject based on the ideXlab platform.
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concordance between patient self reports and claims data on clinical diagnoses medication use and health system utilization in taiwan
PLOS ONE, 2014Co-Authors: Chishin Wu, Shengchang Wang, Huiju TsaiAbstract:Purpose The aim of this study was to evaluate the concordance between claims records in the National Health Insurance Research Database and patient self-reports on clinical diagnoses, medication use, and health system utilization. Methods In this study, we used the data of 15,574 participants collected from the 2005 Taiwan National Health Interview Survey. We assessed positive agreement, negative agreement, and Cohen's kappa statistics to examine the concordance between claims records and patient self-reports. Results Kappa values were 0.43, 0.64, and 0.61 for clinical diagnoses, medication use, and health system utilization, respectively. Using a strict algorithm to identify the clinical diagnoses recorded in claims records could improve the negative agreement; however, the effect on positive agreement and kappa was diverse across various conditions. Conclusion We found that the overall concordance between claims records in the National Health Insurance Research Database and patient self-reports in the Taiwan National Health Interview Survey was moderate for clinical diagnosis and substantial for both medication use and health system utilization.
Mechthild Neises - One of the best experts on this subject based on the ideXlab platform.
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Does the occurrence of adverse life events in patients with breast cancer lead to a change in illness behaviour?
Supportive Care in Cancer, 2008Co-Authors: Siegfried Geyer, Dorothee Noeres, Mariya Mollova, Heike Sassmann, Alexandra Prochnow, Mechthild NeisesAbstract:Goals of work It was examined whether life-changing events may lead to changes of illness behaviour in women prior to breast cancer diagnosis. We considered the delay in three different aspects: date of breast self-examination, routine visits at the doctor, and finally changes in the length of time intervals between the detection of suspicious breast symptoms and the subsequent verification of diagnoses. Materials and methods The data of 240 patients (age
V. A. Vedeshenkov - One of the best experts on this subject based on the ideXlab platform.
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An approach to Self-Diagnosis of nonuniform digital systems
Automation and Remote Control, 2020Co-Authors: V. A. VedeshenkovAbstract:An approach to Self-Diagnosis of the components (modules and communication lines) of nonuniform digital systems consisting of equal numbers of modules of two types (processor, memory) was presented. To carry out checking and Self-Diagnosis, different connected modules are regarded as subsystems which are checked by the active modules such as processors. Bit-stuck multiple failures of a limited number of component are permitted, whereas no new failures occur in the course of Self-Diagnosis. The Barsi-Grandoni-Maestrini model is used to describe the results of subsystem testing. It was assumed that the nonuniform system includes a diagnostic monitor initiating checking and Self-Diagnosis. An example of checking and Self-Diagnosis of the components of a nonuniform 14-module system was presented.
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An approach to Self-Diagnosis of a newly developed fault in digital systems
Automation and Remote Control, 2005Co-Authors: V. A. VedeshenkovAbstract:An approach to Self-Diagnosis of a newly developed fault in digital systems is developed via the expanding domain principle. A restricted number of stable multiple faults in components and development of one more fault during diagnosis are admissible. Self-Diagnosis is initiated twice and the results generated in these starts are compared for detecting the developed fault and obtaining reliable diagnosis. An example is given to illustrate the Self-Diagnosis process in a 9-module system.
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A route-oriented Self-Diagnosis method for digital systems
Automation and Remote Control, 2005Co-Authors: V. A. VedeshenkovAbstract:A route-oriented Self-Diagnosis method for the technical state of modules and connection lines of digital systems is designed. It uses 0-routes for choosing testing modules and transferring test results. Self-Diagnosis is subdivided into two stages: determination of a reliably operative module for starting Self-Diagnosis and Self-Diagnosis of the state of other components of the system. Test results for modules are described with the Preparat-Metze-Chien model. Two examples on Self-Diagnosis of failed components in a 9-module system are given.
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Self-Diagnosis of Digital Systems
Automation and Remote Control, 2003Co-Authors: V. A. VedeshenkovAbstract:Organization of distributed Self-Diagnosis of the components (modules and communication lines) of digital systems on the basis of the Barsi–Grandoni–Maestrini diagnostic model was described. It includes the following components: execution by an operable module of the functions of checking modules, determination of a path from one operable module to another operable module, and processing and decoding of the test results. For Self-Diagnosis of the failed components in a four-dimensional hypercube, two examples illustrating the distinctive features of the procedures were presented.
Hitoshi Kumagai - One of the best experts on this subject based on the ideXlab platform.
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Health Monitoring of Concrete Structures Using Self-Diagnosis Materials
Sensing Issues in Civil Structural Health Monitoring, 2020Co-Authors: H. Inada, Y. Okuhara, Hitoshi KumagaiAbstract:The authors have been continuously conducting a series of research on the development of the fiber reinforced composites as Self-Diagnosis materials. The fiber reinforced composite, which is the glass fiber reinforced plastics containing carbon particles to give electrical conductivity, has been confirmed to possess excellent sensitivity as Self-Diagnosis material. With the aim of developing the technology for maintaining safety of civil infrastructures, several types of Self-Diagnosis materials have been developed for the monitoring sensor to detect damage to structures. Subsequently, the applicability of the Self-Diagnosis materials for the monitoring of the integrity of structures has been evaluated through experimental studies. In this paper, the performance of the proposed Self-Diagnosis materials to detect damage to concrete structures is discussed in detail.
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Experimental study on structural health monitoring of RC columns using Self-Diagnosis materials
Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil Mechanical and Aerospace Systems, 2004Co-Authors: H. Inada, Y. Okuhara, Hitoshi KumagaiAbstract:ABSTRACT The authors have been continuously conducting a series of research works on the development of the fiber reinforced composites as Self-Diagnosis materials. The function to detect damage is based on the property of carbon materials as a conductor of electricity. The conductive fiber reinforced composite, which is the glass fiber reinforced plastics added carbon particles for electrical conductivity, has been confirmed to possess excellent sensitivity as a Self-Diagnosis materials. In this study, a Self-Diagnosis material with the ability to memorize damage history has been applied. Irreversible resistance changes dependent on the strain histories of the composites were utilized to achieve this ability. The authors have also developed an electrically conductive film sensor bonded on the concrete surface to detect cracks and measure crack width. The specimens of the reinforced concrete bridge pier columns were tested under quasi-static cyclic lateral loading. The performance of the proposed Self-Diagnosis materials to detect damage to concrete structures is evaluated through confirmation of the relationship between the extent of damage and the variation of electrical conductivity of Self-Diagnosis materials. On the basis of the obtained experimental results, the applicability of Self-Diagnosis materials to structural health monitoring for concrete structures are discussed in detail, and the practical monitoring techniques for structures are proposed. Keywords: Health monitoring, sensor, carbon particle, concrete, bridge pier column
James J Cimino - One of the best experts on this subject based on the ideXlab platform.
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A learning health care system using computer-aided diagnosis
Journal of Medical Internet Research, 2017Co-Authors: Amos Cahan, James J CiminoAbstract:Physicians intuitively apply pattern recognition when evaluating a patient. Rational diagnosis making requires that clinical patterns be put in the context of disease prior probability, yet physicians often exhibit flawed probabilistic reasoning. Difficulties in making a diagnosis are reflected in the high rates of deadly and costly diagnostic errors. Introduced 6 decades ago, computerized diagnosis support systems are still not widely used by internists. These systems cannot efficiently recognize patterns and are unable to consider the base rate of potential diagnoses. We review the limitations of current computer-aided diagnosis support systems. We then portray future diagnosis support systems and provide a conceptual framework for their development. We argue for capturing physician knowledge using a novel knowledge representation model of the clinical picture. This model (based on structured patient presentation patterns) holds not only symptoms and signs but also their temporal and semantic interrelations. We call for the collection of crowdsourced, automatically deidentified, structured patient patterns as means to support distributed knowledge accumulation and maintenance. In this approach, each structured patient pattern adds to a self-growing and -maintaining knowledge base, sharing the experience of physicians worldwide. Besides supporting diagnosis by relating the symptoms and signs with the final diagnosis recorded, the collective pattern map can also provide disease base-rate estimates and real-time surveillance for early detection of outbreaks. We explain how health care in resource-limited settings can benefit from using this approach and how it can be applied to provide feedback-rich medical education for both students and practitioners.