Remaining issues for the adoption of AI in clinical research

An article entitled “Artificial Intelligence: which services, which applications, which results and which development today in clinical research? Which impacts on the quality of care? Which recommendations?" was published at the end of 2018 in Thérapie by Elsevier

The article was written under the direction of Vincent Diebolt, Director of the French Clinical Research Infrastructure Network (F-CRIN), and also saw the contribution of François-Henri Boissel (Novadiscovery), Avicenna Board Member. It is also to note that the Avicenna’s General Secretary, Thierry Marchal (ANSYS), participated in the Giens XXXIV round table ‘Hot topic N°2’ which contributed to the publication of this article.

This articles discusses the potential of artificial intelligence (AI) to process numerous and heterogenous data and knowledge and to understand potentially complex and abstract rules in the same way as human intelligence can. In particular, it outlines how experts confirmed the potential contribution and  theoretical benefits of AI in healthcare such as in clinical research and patient care efficiency.

The article identifies critical points how AI benefits could be maximized:

1)  Production of tangible demonstrations of the contributions of AI in clinical research by quantifying its benefits;

2)  Building trust to foster dissemination and acceptability of AI in healthcare thanks to an adapted regulatory framework;

3)  Ensuring the availability of technical skills, which implies an investment in training, the attractiveness of the health sector relative to tech-heavy sectors and the development of ergonomic data collection tools for all health operators;

4)  Organisation of a system of governance for a distributed and secure model at the national level to aggregate the information and services existing at the local level.

These four points need to be examined closely as they condition the technical integration and appropriation of AI by all actors of the life science spectrum. As a result, 37 concrete recommendations are presented to enable the adoption of AI in clinical research.

For all of you interested to read it, the article can be found here.


Date: 11/02/2019 | Tag: | News: 903 of 1005
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