Cargando…
Machine learning in medicine: Addressing ethical challenges
Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians.
Autores principales: | Vayena, Effy, Blasimme, Alessandro, Cohen, I. Glenn |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6219763/ https://www.ncbi.nlm.nih.gov/pubmed/30399149 http://dx.doi.org/10.1371/journal.pmed.1002689 |
Ejemplares similares
-
Becoming partners, retaining autonomy: ethical considerations on the development of precision medicine
por: Blasimme, Alessandro, et al.
Publicado: (2016) -
Decentralised clinical trials: ethical opportunities and challenges
por: Vayena, Effy, et al.
Publicado: (2023) -
Big Data and Dementia: Charting the Route Ahead for Research, Ethics, and Policy
por: Ienca, Marcello, et al.
Publicado: (2018) -
Biomedical Big Data: New Models of Control Over Access, Use and Governance
por: Vayena, Effy, et al.
Publicado: (2017) -
New ethical challenges of digital technologies, machine learning and artificial intelligence in public health: a call for papers
por: Zandi, Diana, et al.
Publicado: (2019)