This analysis highlights challenges in deep learning transferability in biosciences, suggesting solutions for reliable evaluation.
Creating generalizable models is a conserved aim in deep learning-however, misleading claims of transferability threaten to obfuscate reliable performance evaluation. We outline the severity of this issue in the biosciences, and suggest potential solutions.
No takes yet. Share an insight, caveat, or question.
O’Shea-Wheller et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: