Opportunities and Challenges for Machine Learning in Rare Diseases.
Front Med (Lausanne)
; 8: 747612, 2021.
Article
em En
| MEDLINE
| ID: mdl-34676229
ABSTRACT
Rare diseases (RDs) are complicated health conditions that are difficult to be managed at several levels. The scarcity of available data chiefly determines an intricate scenario even for experts and specialized clinicians, which in turn leads to the so called "diagnostic odyssey" for the patient. This situation calls for innovative solutions to support the decision process via quantitative and automated tools. Machine learning brings to the stage a wealth of powerful inference methods; however, matching the health conditions with advanced statistical techniques raises methodological, technological, and even ethical issues. In this contribution, we critically point to the specificities of the dialog of rare diseases with machine learning techniques concentrating on the key steps and challenges that may hamper or create actionable knowledge and value for the patient together with some on-field methodological suggestions and considerations.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Aspecto:
Ethics
Idioma:
En
Revista:
Front Med (Lausanne)
Ano de publicação:
2021
Tipo de documento:
Article