Biomedical Imaging's Real Bottleneck Is the Data, Not the Model
Biomedical imaging AI is bottlenecked by data quality and availability, not model architecture
Databricks argues that the primary constraint in biomedical imaging AI is data — its curation, labeling, and accessibility — rather than model sophistication. This reframes the common assumption that better architectures are the path to progress. The insight has practical implications for health systems investing in AI infrastructure.