From Prediction to Intervention: The Evolution of AI in Biomedicine
Artificial intelligence has advanced rapidly in biomedicine through large-scale multimodal data integration, enabling increasingly accurate prediction of clinical outcomes and patient stratification. These systems, however, remain fundamentally observational: they learn statistical associations from historical data and operate within previously observed biological and clinical states, limiting their ability to generalize to novel therapies or unobserved interventions. We argue that AI in biomedicine is undergoing a structural transition. As biomedical decision-making increasingly depends on reasoning about intervention rather than extrapolation from past observations, predictive architect...
| Authors | Andrew Feinberg, Aleksandr Sarachakov, Viktor Svekolkin et al. |
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| Primary category | cs.CY |
| Published | 14 April 2026 |
| Last updated at source | 26 May 2026 |
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