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Título
Flexible Heuristics for Supporting Recommendations Within an AI Platform Aimed at Non-expert Users
Autor(es)
Assunto
Information system
Medical data management
Medical imaging management
Artificial Intelligence
Health platform
HCI
Clasificación UNESCO
1203.17 Informática
1203.04 Inteligencia Artificial
3212 Salud Publica
Fecha de publicación
2023
Resumen
The use of Machine Learning (ML) to resolve complex tasks has
become popular in several contexts. While these approaches are very effective
and have many related benefits, they are still very tricky for the general audience.
In this sense, expert knowledge is crucial to apply ML algorithms properly
and to avoid potential issues. However, in some situations, it is not possible to
rely on experts to guide the development of ML pipelines. To tackle this issue,
we present an approach to provide customized heuristics and recommendations
through a graphical platform to build ML pipelines, namely KoopaML, focused
on the medical domain.With this approach, we aim not only at providing an easy
way to apply ML for non-expert users, but also at providing a learning experience
for them to understand how these methods work.
URI
ISSN
0302-9743
DOI
10.1007/978-3-031-33023-0_30
Aparece en las colecciones
- GRIAL. Artículos [441]