Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities

The evidence-based medicine (EBM) movement is stepping up its efforts to assess medical artificial intelligence (AI) and data science studies. Since 2017, there has been a marked increase in the number of published systematic reviews that assess medical AI studies. Increasingly, data from observatio...

Descripción completa

Detalles Bibliográficos
Autores principales: von Groote, Thilo, Ghoreishi, Narges, Björklund, Maria, Porschen, Christian, Puljak, Livia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Letter
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9238033/
https://www.ncbi.nlm.nih.gov/pubmed/35761303
http://dx.doi.org/10.1186/s13643-022-01984-7
Descripción
Sumario:The evidence-based medicine (EBM) movement is stepping up its efforts to assess medical artificial intelligence (AI) and data science studies. Since 2017, there has been a marked increase in the number of published systematic reviews that assess medical AI studies. Increasingly, data from observational studies are used in systematic reviews of medical AI studies. Assessment of risk of bias is especially important in medical AI studies to detect possible “AI bias”. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13643-022-01984-7.

Ejemplares similares