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Multi-view MRI inputs can enhance spatial localization but may compromise temporal reasoning, revealing critical limitations in current foundation models for clinical use.
CORTEX reveals that structured reasoning in 3D chest CT MLLMs can enhance diagnostic transparency and reliability, bridging a significant gap in medical imaging AI.
GMM pooling not only enhances preterm birth prediction accuracy but also sets a new standard for image-based classification tasks by effectively modeling intra-patient variability.
Top algorithms in the HECKTOR 2025 challenge achieved impressive segmentation and survival prediction metrics, showcasing the power of multimodal imaging in oncology.
Reliable Earth-science agents need to master the orchestration of diverse data sources and workflows, not just tool access.
A novel knowledge distillation technique allows a tiny 11M parameter model to not just match, but *beat* a 300M parameter foundation model on fetal ultrasound tasks, opening the door to real-time AI on handheld devices.
