Aviso: Este site agrega dados públicos oficiais da FDA, ClinicalTrials.gov, PubMed e SEC EDGAR apenas para referência geral. Não constitui aconselhamento médico, diagnóstico, recomendação de tratamento ou aconselhamento de investimento.

PubMed

Machine Learning-Enabled Medical Devices Authorized by the US Food and Drug Administration in 2024: Regulatory Characteristics, Predicate Lineage, and Transparency Reporting.

PMID: 41463017 ·

B, a, s, s, e, l, , A, l, m, a, r, i, e, ;, , L, u, i, s, , F, e, r, n, a, n, d, o, , G, o, n, z, a, l, e, z, -, G, o, n, z, a, l, e, z, ;, , L, u, c, a, s, , A, n, t, ô, n, i, o, , D, o, s, , S, a, n, t, o, s, , B, a, r, b, o, s, a, ;, , A, m, e, l, i, e, , L, u, t, z, ;, , U, l, r, i, c, h, , G, r, o, s, s, e, ;, , F, e, l, i, p, e, , F, r, e, g, n, i

RevistaBiomedicines
Ano
PMID41463017

Resumo

Background: The US Food and Drug Administration (FDA) authorized over 690 machine learning (ML)-enabled medical devices between 1995 and 2023. In 2024, new guidance enabled the inclusion of Predetermined Change Control Plans (PCCPs), raising expectations for transparency, equity, and safety under the Good Machine Learning Practice (GMLP) framework. Objective: The objective was to assess regulatory pathways, predicate lineage, demographic transparency, performance reporting, and PCCP uptake among

Fonte oficial

Ver no PubMed →

Dados provenientes do PubMed / NCBI. Para consultar o texto integral e as informações mais recentes, recorra sempre ao registo oficial.

↑