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Review : Autosomal Dominant Polycystic Kidney Disease: 2009 Update for Internists
William M. Bennett 대한내과학회 2009 The Korean Journal of Internal Medicine Vol.24 No.3
Because autosomal dominant polycystic kidney disease (ADPKD) is one of the most common genetic abnormalities seen in today`s medical practice, many internists will likely treat patients affected by this condition. Genetic abnormalities have been increasingly recognized, and the pathophysiology of the disease is beginning to be unraveled. Because of advances in imaging technology, surrogate markers for disease progression have allowed clinical studies of newer therapeutic agents to proceed. In the near future, therapies for this common genetic disease may be available to either prevent or stabilize the disease course for many affected individuals. (Korean J Intern Med 2009;24:165-168)
Direct Ritz method for random seismic response for non-uniform beams
Lin, J.H.,Williams, F.W.,Bennett, P.N. Techno-Press 1994 Structural Engineering and Mechanics, An Int'l Jou Vol.2 No.3
Based on a fast and accurate method for the stationary random seismic response analysis for discretized structures(Lin 1992, Lin et al. 1992), a Ritz method for dealing with such responses of continuous systems in developed. This method is studied quantitatively, using cantilever shear beams for simplicity and clarity. The process can be naturally extended to deal with various boundary conditions as well as non-uniform Bernoulli-Euler beams, or even Timoshenko beams. Algorithms for both proportionally and non-proportionally damped responses are described. For all of such damping cases, it is not necessary to solve for the natural vibrations of the beams. The solution procedure is very simple, and equally efficient for a white or a non-white ground excitation spectrum. Two examples are given where various power spectral density functions, variances, covariances and second spectral moments of displacement, internal force response, and their derivatives are calculated and analyses. Some Ritz solutions are compared with "exact" CQC solutions.
API Driven On-Demand Participant ID Pseudonymization in Heterogeneous Multi-Study Research
Shorabuddin Syed,Mahanazuddin Syed,Hafsa Bareen Syeda,Maryam Garza,William Bennett,Jonathan Bona,Salma Begum,Ahmad Baghal,Meredith Zozus,Fred Prior 대한의료정보학회 2021 Healthcare Informatics Research Vol.27 No.1
Objectives: To facilitate clinical and translational research, imaging and non-imaging clinical data from multiple disparatesystems must be aggregated for analysis. Study participant records from various sources are linked together and to patient recordswhen possible to address research questions while ensuring patient privacy. This paper presents a novel tool that pseudonymizesparticipant identifiers (PIDs) using a researcher-driven automated process that takes advantage of application-programminginterface (API) and the Perl Open-Source Digital Imaging and Communications in Medicine Archive (POSDA) tofurther de-identify PIDs. The tool, on-demand cohort and API participant identifier pseudonymization (O-CAPP), employsa pseudonymization method based on the type of incoming research data. Methods: For images, pseudonymization of PIDsis done using API calls that receive PIDs present in Digital Imaging and Communications in Medicine (DICOM) headersand returns the pseudonymized identifiers. For non-imaging clinical research data, PIDs provided by study principal investigators(PIs) are pseudonymized using a nightly automated process. The pseudonymized PIDs (P-PIDs) along with other protectedhealth information is further de-identified using POSDA. Results: A sample of 250 PIDs pseudonymized by O-CAPPwere selected and successfully validated. Of those, 125 PIDs that were pseudonymized by the nightly automated process werevalidated by multiple clinical trial investigators (CTIs). For the other 125, CTIs validated radiologic image pseudonymizationby API request based on the provided PID and P-PID mappings. Conclusions: We developed a novel approach of an ondemandpseudonymization process that will aide researchers in obtaining a comprehensive and holistic view of study participantdata without compromising patient privacy.