nnMIL: A generalizable multiple instance learning framework for computational pathology
PositiveArtificial Intelligence
- nnMIL has been developed as a versatile multiple
- This advancement is significant as it addresses existing limitations in feature aggregation, enhancing diagnostic accuracy and treatment guidance in clinical settings.
- The development reflects a broader trend in computational pathology towards integrating advanced AI models, with ongoing efforts to improve diagnostic capabilities and address challenges in accuracy and generalizability.
— via World Pulse Now AI Editorial System
