scholarly journals Application of Big Data in the medical technology evaluation process

2021 ◽  
Vol 96 ◽  
pp. 01011
Author(s):  
Lei Feng ◽  
Juxiu Huang ◽  
Jingxing Liao

The evaluation of public satisfaction with government quality work is an evaluation form to evaluate government performance from the perspective of the public. The evaluation process is open and transparent, and the results are relatively objective and fair. Taking the application practice in Nei Mongol as an example, in this paper, an index framework is designed and constructed, 12 leagues and cities in the whole region are covered by the investigation, and the actual effect of local quality work is explored and analyzed in combination with big data technology so as to provide enlightenment and reference for relevant research work in the quality field.


2017 ◽  
pp. 41-64
Author(s):  
Marta Padilla-Ruiz ◽  
Carlos López-Vázquez

We are immersed in the Big Data era, where there is a large amount of heterogeneous data, both in time and spatial scales. This data starts to be streamed in real time from different devices and sensors, well illustrated by the new concept of Smart Cities. Conflation processes play an important role in this scenario, defined as the procedure for the combination and integration of different data sources, improving the level of information of the result. It also allows to update geographical databases (GDB), conflating different kind of sources where one of them is more accurate or updated than the other. Regarding geometric conflation, the procedure involves transforming features from one data source to another, minimizing the geometric discrepancies between them. Accuracy has to be taken into account in these processes, and the results need to be measured and evaluated in order to have a better understanding of product quality. In this paper, conflation evaluation process is described along with the different metrics and approaches to assess its accuracy.


2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Jeffrey M. Keisler ◽  
Benjamin D. Trump ◽  
Emily Wells ◽  
Igor Linkov

AbstractTechnology innovation is inherently uncertain. The risk–benefit divide for such innovation is a classical debate within scholarly literature and is often framed on a monetary scale where innovation approval is granted if benefit outweighs risk. However, such discussion leaves out a critical yet subjective vein of discussion within the innovation evaluation process — stakeholder context. Specifically, regulators and technology developers are often described as having respective motivations that are often at odds with one another. In theory, efforts towards balancing risk and benefit for technology evaluation should be driven by relatively efficient, inexpensive, robust methods, and processes. In practice, however, technology evaluation is often expensive, slow, and often of questionable quality for new and emerging technologies. Literature often frames the innovation-regulation tradeoff as a zero-sum game driven by regulators and developers that are inherently at odds with one another. However, we argue that such a relationship is actually worse than zero-sum and is a classic framing problem as described by Kahneman and Tversky. Specifically, the divergent frames adopted by regulators and technology developers, respectively, can drastically affect their perception of risk and tolerance for further development and commercialization of a given technology. There are known and natural solutions to such problems that can smooth the path towards realizing the societal potential of emerging technologies.


Sign in / Sign up

Export Citation Format

Share Document