ABSTRACT
Following the emergence of open public databases and connected objects, big data and artificial intelligence are developing rapidly, especially in medicine, with many opportunities ranging from complex diagnostic assistance to real-time statistical analysis. In order to promote their development and guide their use in the field of internal medicine, guidelines and recommendations are needed. First of all, this article seeks to clarify the concepts of big data and artificial intelligence and the correlations between each other, and then to give an overview of the progress made at European level in this rapidly expanding field.
Subject(s)
Artificial Intelligence/standards , Internal Medicine/standards , Practice Guidelines as Topic , Artificial Intelligence/supply & distribution , Big Data , Databases, Factual , Education, Medical, Continuing/trends , Humans , Internal Medicine/education , Internal Medicine/methods , Internal Medicine/trends , Physicians/standards , Physicians/trends , Practice Patterns, Physicians'/standards , Practice Patterns, Physicians'/trendsABSTRACT
We report on an alternative route based on nanomechanical folding induced by an AFM tip to obtain weakly interacting multilayer graphene (wi-MLG) from a chemical vapor deposition (CVD)-grown single-layer graphene (SLG). The tip first cuts and then pushes and folds graphene during zigzag movements. The pushed graphene has been analyzed using various Raman microscopy plots- AD/ AG × EL4 vs ΓG, ω2D vs Γ2D, Γ2D vs ΓG, ω2D+/- vs Γ2D+/-, and A2D-/ A2D+ vs A2D/ AG. We show that the SLG in-plane properties are maintained under the folding process and that a few tens of graphene layers are stacked, with a limited number of structural defects. A blue shift of about 20 cm-1 of the 2D band is observed. The relative intensity of the 2D- and 2D+ bands have been related to structural defects, giving evidence of their role in the inner and outer processes at play close to the Dirac cone.
