实验表明，即便在数据极度稀疏（例如仅保留30%观测点）的条件下，MIRA的性能依然保持稳健，并未像传统预测模型那样出现性能的显著下滑。这种对真实世界“脏数据”的适应能力，证明了其在复杂临床环境下的高鲁棒性。

在大模型（LLM）与计算机视觉（CV）争相重塑医疗行业的今天，我们似乎已经拥有了无所不能的数字助手：它们能够像放射科医生一样精准解读CT影像，也能像内科医生一样撰写病历摘要。 但医疗AI世界中，仍有一块关键拼图缺失——那就是理解“生命动态演变”的能力。 △图1.不同模态的医疗数据 正如图1所示，如果将患者的生命历程比作一部电影，现有的AI往往只能捕捉到零散的帧画： 唯有时间序列（Time Seri ...

据这家瑞士公司介绍，AI Design Copilot 能够将数周的手动计算机辅助设计（CAD）工作压缩到几分钟内，快速评估数百万个设计变体，从而将重新设计工作减少多达50%。Neural ...

For the past decade, AI researcher Chris Olah has been obsessed with artificial neural networks. One question in particular engaged him, and has been the center of his work, first at Google Brain, ...

Researchers at the Yong Loo Lin School of Medicine, National University of Singapore (NUS Medicine), have found that a key ...

The human brain is complex. Understanding deep brain function usually requires the insertion of probes that frequently result ...

LAUSANNE, Switzerland--(BUSINESS WIRE)--Neural Concept, the leading Engineering Intelligence platform that transforms product design with 3D Deep Learning, has announced that it has raised $27 million ...

Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...