Reproducing Protocol‐Based Studies Using Parameterizable Tools—Comparison of Analytic Approaches Used by Two Medical Product Surveillance Networks

2020 ◽  
Vol 107 (4) ◽  
pp. 966-977 ◽  
Author(s):  
Ting‐Ying Huang ◽  
Emily C. Welch ◽  
Mayura U. Shinde ◽  
Robert W. Platt ◽  
Kristian B. Filion ◽  
...  
2017 ◽  
Vol 4 (4) ◽  
pp. 298-306 ◽  
Author(s):  
John G. Connolly ◽  
Shirley V. Wang ◽  
Candace C. Fuller ◽  
Sengwee Toh ◽  
Catherine A. Panozzo ◽  
...  

Author(s):  
Roselie A. Bright ◽  
Marilyn N. Flack ◽  
Susan N. Gardner

1995 ◽  
Vol 34 (05) ◽  
pp. 518-522 ◽  
Author(s):  
M. Bensadon ◽  
A. Strauss ◽  
R. Snacken

Abstract:Since the 1950s, national networks for the surveillance of influenza have been progressively implemented in several countries. New epidemiological arguments have triggered changes in order to increase the sensitivity of existent early warning systems and to strengthen the communications between European networks. The WHO project CARE Telematics, which collects clinical and virological data of nine national networks and sends useful information to public health administrations, is presented. From the results of the 1993-94 season, the benefits of the system are discussed. Though other telematics networks in this field already exist, it is the first time that virological data, absolutely essential for characterizing the type of an outbreak, are timely available by other countries. This argument will be decisive in case of occurrence of a new strain of virus (shift), such as the Spanish flu in 1918. Priorities are now to include other existing European surveillance networks.


Author(s):  
Jessica M. Franklin ◽  
Kai‐Li Liaw ◽  
Solomon Iyasu ◽  
Cathy Critchlow ◽  
Nancy Dreyer

2021 ◽  
Vol 2 (5) ◽  
Author(s):  
Tuomas Granlund ◽  
Vlad Stirbu ◽  
Tommi Mikkonen

AbstractAgile software development embraces change and manifests working software over comprehensive documentation and responding to change over following a plan. The ability to continuously release software has enabled a development approach where experimental features are put to use, and, if they stand the test of real use, they remain in production. Examples of such features include machine learning (ML) models, which are usually pre-trained, but can still evolve in production. However, many domains require more plan-driven approach to avoid hazard to environment and humans, and to mitigate risks in the process. In this paper, we start by presenting continuous software engineering practices in a regulated context, and then apply the results to the emerging practice of MLOps, or continuous delivery of ML features. Furthermore, as a practical contribution, we present a case study regarding Oravizio, first CE-certified medical software for assessing the risks of joint replacement surgeries. Towards the end of the paper, we also reflect the Oravizio experiences to MLOps in regulatory context.


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