🔬 Training Transformers to solve 95% failure rate of Cancer Trials the AI for Science pod is back...
TL;DR · AI 摘要
Noetik团队正用Transformer模型TARIO-2处理肿瘤空间转录组数据，试图解决癌症临床试验95%失败率问题，聚焦患者筛选等关键瓶颈。
核心要点
- TARIO-2是基于全球最大肿瘤空间转录组数据集训练的自回归Transformer模型。
- 项目核心目标是通过AI优化患者筛选，降低癌症临床试验高失败率。
- 成功依赖前期多年高质量数据积累，体现数据基础对AI医疗的关键性。
the AI for Science pod is back with @RonAlfa, CEO of @NOETIK_ai, and Daniel Bear, VP Research at Noetik, explaining exactly how their team of top AI x Bio researchers and engineers (shoutout @owl_posting) will https://t.co/xdyYWraTkU" / X
Latent.Space on X: "🔬 Training Transformers to solve 95% failure rate of Cancer Trials the AI for Science pod is back with @RonAlfa, CEO of @NOETIK_ai, and Daniel Bear, VP Research at Noetik, explaining exactly how their team of top AI x Bio researchers and engineers (shoutout @owl_posting) will https://t.co/xdyYWraTkU" / X
Don’t miss what’s happening
Training Transformers to solve 95% failure rate of Cancer Trials the AI for Science pod is back with
, CEO of
, and Daniel Bear, VP Research at Noetik, explaining exactly how their team of top AI x Bio researchers and engineers (shoutout
) will use AI to cure cancer, by focusing on key bottlenecks like patient selection, and training large cancer foundation models like TARIO-2, an autoregressive transformer trained on one of the largest sets of tumor spatial transcriptomics datasets in the world... which first required years of blind faith in collecting good data to even get going:
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