Aviso: Este sitio agrega datos públicos oficiales de la FDA, ClinicalTrials.gov, PubMed y SEC EDGAR solo como referencia general. No constituye asesoramiento médico, diagnóstico, recomendaciones de tratamiento ni asesoramiento de inversión.

PubMed

Regulatory oversight, causal inference, and safe and effective health care machine learning.

PMID: 31742358 ·

A, r, i, e, l, , D, o, r, a, , S, t, e, r, n, ;, , W, , N, i, c, h, o, l, s, o, n, , P, r, i, c, e

RevistaBiostatistics (Oxford, England)
Año
PMID31742358

Resumen

In recent years, the applications of Machine Learning (ML) in the health care delivery setting have grown to become both abundant and compelling. Regulators have taken notice of these developments and the U.S. Food and Drug Administration (FDA) has been engaging actively in thinking about how best to facilitate safe and effective use. Although the scope of its oversight for software-driven products is limited, if FDA takes the lead in promoting and facilitating appropriate applications of causal

Fuente oficial

Ver en PubMed →

Datos obtenidos de PubMed / NCBI. Para consultar el texto completo y la información más reciente, remítase siempre al registro oficial.

↑