EN BREF ...
"The rapid increase of interest in, and use of, artificial intelligence (AI) in computer applications has raised a parallel concern about its ability (or lack thereof) to provide understandable, or explainable, output to users. This concern is especially legitimate in biomedical contexts, where patient safety is of paramount importance. This position paper brings together seven researchers working in the field with different roles and perspectives, to explore in depth the concept of explainable AI, or XAI, offering a functional definition and conceptual framework or model that can be used when considering XAI. This is followed by a series of desiderata for attaining explainability in AI, each of which touches upon a key domain in biomedicine." En bref issu de l'étude.
Rédacteur(s) de la fiche : Beesens TEAM
Introductio
1 - In tincidunt nunc ac velit tristique
- Pellentesque congue, magna elementum suscipit vestibulum
- Aenean eleifend sodales ipsum vitae consequat
- Quisque est leo tempus vel purus eu, placerat tincidunt nisl
2 - Sed lobortis elit vitae mollis consectetur
- In tincidunt nunc ac velit tristique
- Donec accumsan elit ac ornare eleifend
- Sed pellentesque suscipit quam ut finibus
- Fusce imperdiet neque sit amet ipsum ullamcorper scelerisque
3 - Lorem ipsum dolor sit amet
- Pellentesque congue, magna elementum suscipit vestibulum
- Aenean eleifend sodales ipsum vitae consequat
- Quisque est leo tempus vel purus eu, placerat tincidunt nisl
Conclusio
Pour accéder à ce contenu,
créez votre compte
gratuitement
Accéder à :
- L'ensemble de la veille e-santé sélectionnée
par la communauté Beesens, - Des documents de références de la e-santé,
- Et bien plus encore...
Déjà inscrit ? Identifiez-vous