
doi: 10.1002/eahr.500181
pmid: 37777978
ABSTRACTImpactful translational research requires new approaches to computational analysis and bioethics, both of which have been advanced by adoption of community‐engagement strategies. Community knowledge and experience will hone data collection, research, and insights and accelerate the impact of derived translational applications to improve individual health, medical decision‐making, and public health policy. In the context of translational research with big health data, meaningful community‐researcher engagement will require developing and deploying coengagement tools across the research life cycle and developing approaches for novel coproduction.
Translational Research, Biomedical, Data Collection, Humans
Translational Research, Biomedical, Data Collection, Humans
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
