Events MOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed.

Event submissions

Published

This submission belongs to the session 09. TECHLAWSCI-03: PANELFIT & NKL H2020 Tech. Law. & Sci. Challenges, Bilbao, Spain, Halden, Norway, Baltimore, USA, 2021 of the event MOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed.

Published date

07 Aug, 2019

Citation

Ricardo Santana, Robin Zuluaga, Piedad Gañán, Enrique Onieva, Sonia Arrasate, Machine Learning: The Way for Improving Law Application, in Proceedings of MOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed., 20 March–20 December 2019, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-05-06248

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Machine Learning: The Way for Improving Law Application

Ricardo Santana ¹

Robin Zuluaga ²

Piedad Gañán ²

Enrique Onieva ³

Sonia Arrasate ⁴

1. University of Deusto / Universidad Pontificia Bolivariana

2. Universidad Pontificia Bolivariana

3. University of Deusto

4. Universidad del País Vasco

Abstract

The study was carried out to show how the Precautionary Principle is better applied with Machine Learning techniques. The development of Machine Learning techniques and the wider application for different disciplines, such as Biotechnology, Nanotechnology, and Science of Materials, has been increasing in recent years.Modelling and simulation techniques should be promoted for regulation assessment, taking into consideration the uncertainty of new compounds product of biotechnology and nanotechnology applications.

Keywords

Machine Learning

Regulation

Manuscript

USEDAT MOL2NET 2019.pdf

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