46,643 research outputs found
Model-based Recursive Partitioning for Subgroup Analyses
The identification of patient subgroups with differential treatment effects
is the first step towards individualised treatments. A current draft guideline
by the EMA discusses potentials and problems in subgroup analyses and
formulated challenges to the development of appropriate statistical procedures
for the data-driven identification of patient subgroups. We introduce
model-based recursive partitioning as a procedure for the automated detection
of patient subgroups that are identifiable by predictive factors. The method
starts with a model for the overall treatment effect as defined for the primary
analysis in the study protocol and uses measures for detecting parameter
instabilities in this treatment effect. The procedure produces a segmented
model with differential treatment parameters corresponding to each patient
subgroup. The subgroups are linked to predictive factors by means of a decision
tree. The method is applied to the search for subgroups of patients suffering
from amyotrophic lateral sclerosis that differ with respect to their Riluzole
treatment effect, the only currently approved drug for this disease.Comment: 26 pages, 6 figure
The potential of additive manufacturing in the smart factory industrial 4.0: A review
Additive manufacturing (AM) or three-dimensional (3D) printing has introduced a novel production method in design, manufacturing, and distribution to end-users. This technology has provided great freedom in design for creating complex components, highly customizable products, and efficient waste minimization. The last industrial revolution, namely industry 4.0, employs the integration of smart manufacturing systems and developed information technologies. Accordingly, AM plays a principal role in industry 4.0 thanks to numerous benefits, such as time and material saving, rapid prototyping, high efficiency, and decentralized production methods. This review paper is to organize a comprehensive study on AM technology and present the latest achievements and industrial applications. Besides that, this paper investigates the sustainability dimensions of the AM process and the added values in economic, social, and environment sections. Finally, the paper concludes by pointing out the future trend of AM in technology, applications, and materials aspects that have the potential to come up with new ideas for the future of AM explorations
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