The Experts below are selected from a list of 153 Experts worldwide ranked by ideXlab platform
Lucinda Pfalzer - One of the best experts on this subject based on the ideXlab platform.
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cancer rehabilitation publications 2008 2018 with a focus on physical function a scoping review
Physical Therapy, 2020Co-Authors: Shana Harrington, Nicole L Stout, Elizabeth Hile, Mary Insana Fisher, Melissa M Eden, Victoria G Marchese, Lucinda PfalzerAbstract:BACKGROUND Cancer rehabilitation research has accelerated over the last decade. However, closer examination of the published literature reveals that the majority of this work has focused on psychological interventions and cognitive and behavioral therapies. Recent initiatives have aggregated expert consensus around research priorities, highlighting a dearth in research regarding measurement of and interventions for physical function. Increasingly loud calls for the need to address the myriad of physical functional impairments that develop in people living with and beyond cancer have been published in the literature. A detailed survey of the landscape of published research has not been reported to our knowledge. PURPOSE This scoping review systematically identified literature published between 2008 and 2018 related to the screening, assessment, and interventions associated with physical function in people living with and beyond cancer. DATA SOURCES PubMed and CINAHL were searched up to September 2018. STUDY SELECTION Study selection included articles of all levels of evidence on any disease stage and population. A total of 11,483 articles were screened for eligibility, 2507 full-text articles were reviewed, and 1055 articles were selected for final inclusion and extraction. DATA EXTRACTION Seven reviewers recorded type of cancer, disease stage, age of participants, phase of treatment, time since Diagnosis, Application to physical function, study design, impairments related to physical function, and measurement instruments used. DATA SYNTHESIS Approximately one-third of the articles included patients with various cancer diagnoses (30.3%), whereas the rest focused on a single cancer, most commonly breast (24.8%). Most articles (77%) measured physical function following the completion of active cancer treatment with 64% representing the assessment domain. The most commonly used measures of physical function were the Medical Outcomes Study 36-Item Health Survey Questionnaire (29%) and the European Organization for Research and Treatment of cancer Quality of Life Questionnaire-Cancer 30 (21.5%). LIMITATIONS Studies not written in English, study protocols, conference abstracts, and unpublished data were excluded. CONCLUSIONS This review elucidated significant inconsistencies in the literature regarding language used to define physical function, measurement tools used to characterize function, and the use of those tools across the cancer treatment and survivorship trajectory. The findings suggested that physical function in cancer research is predominantly measured using general health-related quality-of-life tools rather than more precise functional assessment tools. Interdisciplinary and clinician-researcher collaborative efforts should be directed toward a unified definition and assessment of physical function.
Michael Pecht - One of the best experts on this subject based on the ideXlab platform.
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a hybrid feature selection scheme for reducing diagnostic performance deterioration caused by outliers in data driven diagnostics
IEEE Transactions on Industrial Electronics, 2016Co-Authors: Myeongsu Kang, Md Rashedul Islam, Michael PechtAbstract:In practice, outliers, defined as data points that are distant from the other agglomerated data points in the same class, can seriously degrade diagnostic performance. To reduce diagnostic performance deterioration caused by outliers in data-driven diagnostics, an outlier-insensitive hybrid feature selection (OIHFS) methodology is developed to assess feature subset quality. In addition, a new feature evaluation metric is created as the ratio of the intraclass compactness to the interclass separability estimated by understanding the relationship between data points and outliers. The efficacy of the developed methodology is verified with a fault Diagnosis Application by identifying defect-free and defective rolling element bearings under various conditions.
Lei Deng - One of the best experts on this subject based on the ideXlab platform.
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fault Diagnosis for a wind turbine transmission system based on manifold learning and shannon wavelet support vector machine
Renewable Energy, 2014Co-Authors: Baoping Tang, Tao Song, Feng Li, Lei DengAbstract:Fault Diagnosis for wind turbine transmission systems is an important task for reducing their maintenance cost. However, the non-stationary dynamic operating conditions of wind turbines pose a challenge to fault Diagnosis for wind turbine transmission systems. In this paper, a novel fault Diagnosis method based on manifold learning and Shannon wavelet support vector machine is proposed for wind turbine transmission systems. Firstly, mixed-domain features are extracted to construct a high-dimensional feature set characterizing the properties of non-stationary vibration signals from wind turbine transmission systems. Moreover, an effective manifold learning algorithm with non-linear dimensionality reduction capability, orthogonal neighborhood preserving embedding (ONPE), is applied to compress the high-dimensional feature set into low-dimensional eigenvectors. Finally, the low-dimensional eigenvectors are inputted into a Shannon wavelet support vector machine (SWSVM) to recognize faults. The performance of the proposed method was proved by successful fault Diagnosis Application in a wind turbine's gearbox. The Application results indicated that the proposed method improved the accuracy of fault Diagnosis.
Shana Harrington - One of the best experts on this subject based on the ideXlab platform.
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cancer rehabilitation publications 2008 2018 with a focus on physical function a scoping review
Physical Therapy, 2020Co-Authors: Shana Harrington, Nicole L Stout, Elizabeth Hile, Mary Insana Fisher, Melissa M Eden, Victoria G Marchese, Lucinda PfalzerAbstract:BACKGROUND Cancer rehabilitation research has accelerated over the last decade. However, closer examination of the published literature reveals that the majority of this work has focused on psychological interventions and cognitive and behavioral therapies. Recent initiatives have aggregated expert consensus around research priorities, highlighting a dearth in research regarding measurement of and interventions for physical function. Increasingly loud calls for the need to address the myriad of physical functional impairments that develop in people living with and beyond cancer have been published in the literature. A detailed survey of the landscape of published research has not been reported to our knowledge. PURPOSE This scoping review systematically identified literature published between 2008 and 2018 related to the screening, assessment, and interventions associated with physical function in people living with and beyond cancer. DATA SOURCES PubMed and CINAHL were searched up to September 2018. STUDY SELECTION Study selection included articles of all levels of evidence on any disease stage and population. A total of 11,483 articles were screened for eligibility, 2507 full-text articles were reviewed, and 1055 articles were selected for final inclusion and extraction. DATA EXTRACTION Seven reviewers recorded type of cancer, disease stage, age of participants, phase of treatment, time since Diagnosis, Application to physical function, study design, impairments related to physical function, and measurement instruments used. DATA SYNTHESIS Approximately one-third of the articles included patients with various cancer diagnoses (30.3%), whereas the rest focused on a single cancer, most commonly breast (24.8%). Most articles (77%) measured physical function following the completion of active cancer treatment with 64% representing the assessment domain. The most commonly used measures of physical function were the Medical Outcomes Study 36-Item Health Survey Questionnaire (29%) and the European Organization for Research and Treatment of cancer Quality of Life Questionnaire-Cancer 30 (21.5%). LIMITATIONS Studies not written in English, study protocols, conference abstracts, and unpublished data were excluded. CONCLUSIONS This review elucidated significant inconsistencies in the literature regarding language used to define physical function, measurement tools used to characterize function, and the use of those tools across the cancer treatment and survivorship trajectory. The findings suggested that physical function in cancer research is predominantly measured using general health-related quality-of-life tools rather than more precise functional assessment tools. Interdisciplinary and clinician-researcher collaborative efforts should be directed toward a unified definition and assessment of physical function.
Fuyuan Xiao - One of the best experts on this subject based on the ideXlab platform.
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divergence measure of pythagorean fuzzy sets and its Application in medical Diagnosis
Applied Soft Computing, 2019Co-Authors: Fuyuan Xiao, Weiping DingAbstract:Abstract The Pythagorean fuzzy set (PFS) which is an extension of intuitionistic fuzzy set, is more capable of expressing and handling the uncertainty under uncertain environments, so that it was broadly applied in a variety of fields. Whereas, how to measure PFSs’ distance appropriately is still an open issue. It is well known that the square root of Jensen–Shannon divergence is a true metric in the probability distribution space which is a useful measure of distance. On account of this point, a novel divergence measure between PFSs is proposed by taking advantage of the Jensen–Shannon divergence in this paper, called as PFSJS distance. This is the first work to consider the divergence of PFSs for measuring the discrepancy of data from the perspective of the relative entropy. The new PFSJS distance measure has some desirable merits, in which it meets the distance measurement axiom and can better indicate the discrimination degree of PFSs. Then, numerical examples demonstrate that the PFSJS distance can avoid generating counter-intuitive results which is more feasible, reasonable and superior than existing distance measures. Additionally, a new algorithm based on the PFSJS distance measure is designed to solve the problems of medical Diagnosis. By comparing the different methods in the medical Diagnosis Application, it is found that the new algorithm is as efficient as the other methods. These results prove that the proposed method is practical in dealing with the medical Diagnosis problems.
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a hybrid fuzzy soft sets decision making method in medical Diagnosis
IEEE Access, 2018Co-Authors: Fuyuan XiaoAbstract:The existing approaches for fuzzy soft sets decision-making are mainly based on different types of level soft sets. How to deal with such kinds of fuzzy soft sets decision-making problems via decreasing the uncertainty resulting from human’s subjective cognition is still an open issue. To address this issue, a hybrid method for utilizing fuzzy soft sets in decision-making by integrating a fuzzy preference relations analysis based on the belief entropy with the Dempster–Shafer evidence theory is proposed. The proposed method is composed of four procedures. First, we measure the uncertainties of parameters by leveraging the belief entropy. Second, with the fuzzy preference relations analysis, the uncertainties of parameters are modulated by making use of the relative reliability preference of parameters. Third, an appropriate basic probability assignment in terms of each parameter is generated on the modulated uncertainty degrees of parameters basis. Finally, we adopt Dempster’s combination rule to fuse the independent parameters into an integrated one; thus, the best one can be obtained based on the ranking candidate alternatives. In order to validate the feasibility and effectiveness of the proposed method, a numerical example and a medical Diagnosis Application are implemented. From the experimental results, it is demonstrated that the proposed method outperforms the related methods, because the uncertainty resulting from human’s subjective cognition can be reduced; meanwhile, the decision-making level can also be improved with better performance.