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Background: Parkinson's disease (PD) occurs worldwide but prior to this review of data from the Thailand Parkinson's Disease Registry there had been no nationwide PD registry reported globally. Objective: To determine the distribution and prevalence of PD in Thailand and related risk factors in order to more adequately develop and allocate prevention and treatment resources where they are most needed and to ascertain risk factors that are specific to the Thai population. Design: The Thailand Parkinson's Disease Registry is a new resource, and data collection began in March 2008. Data is collected by the Registry from physicians, and a mechanism is also provided for patients to self-report. This data was further analyzed by the capture-recapture methodology (CRM) to assess reporting biases. Methods: The three main sources of data input to the Registry, i.e. (1) public hospitals, (2) private hospitals and (3) self-registration, require checking for duplicates and also allow estimation of completeness of recording (the degree of underreporting) in this disease registry. There is underreporting because of poor record keeping and administrative procedures in some facilities, and there is an unknown number of persons with PD who are not properly diagnosed because of inadequate facilities and staffing in some areas. Since our data sources should be overlapping in some way, and assuming that the likelihood of being detected in one system is independent of the others, we estimated these data sources' actual coverage and the expected total number of patients utilizing the 'capture-recapture' statistical technique. Results: As of March 2011, the Thailand PD Registry had identified 40,049 PD patients. Employing log-linear modeling, the CRM analysis based on the three data sets estimated underreporting of 20,516 cases. The revised estimated total is thus 60,565 cases, resulting in a crude and age-adjusted prevalence of 95.34 and 424.57 PD cases/100,000 population, respectively. The prevalence of PD was 126.83/100,000 in urban areas and 90.82/100,000 in rural areas (p < 0.001). Preliminary regional comparisons revealed a higher prevalence of PD in residents of the central plain valley of Thailand, an area with a large amount of pesticide use. Conclusions: The combination of a passive registry and the CRM technique allowed us to derive population prevalence estimates for PD in Thailand. Thai PD prevalence estimates were similar to previous ones published for Asian countries; in addition, they suggested that urbanization and exposure to pesticides may both be risk factors for PD in the Thai population. Copyright © 2011 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

We propose a technique for first‐order gradient‐based optimization of stochastic objective functions called Nesterov‐accelerated adaptive moment assessment, which makes use of dynamic evaluations of lower‐order moments. The adaptive moment assessment and the Nesterov acceleration gradient are combined. Consequently, it has perks, and this technique is convenient to use, numerically economical, memory‐light, and very well‐suited for challenges with massive amounts of information and characteristics. Additionally, we investigate the algorithm's convergence characteristics and propose a conservative constraint on the convergence rate. Finally, we employ this technique for the detection and classification of safety helmets. [ABSTRACT FROM AUTHOR]