This question matters as fully automated or AI-assisted scientific loops become common.<p>For example, MDA-MB-435 was a cell line used to study breast cancer for decades, but its origin was disputed for years and eventually confirmed as melanoma.<p>Another open question, one layer above experiments: what is the greatest barrier to curing cancer?<p>Is it disease understanding? [0]<p>Or regulatory reform of clinical trials? [1]<p>Or clinical trial scarcity? [2]<p>Or science upstream of clinical trials, and other factors? [3, 4]<p>Many experts disagree.<p>If machines allocated resources and set priorities, how should they decide what is right?<p>If you want to dive into the challenges of curing cancer, I recommend reading all five sources, starting with [1]. It&#x27;s a New York Times essay w

  • 情报分类：技术价值
  • 命中依据：专家意见分歧时机器如何判断，AI方法论讨论
  • 来源：Hacker News 新项目
  • 原作者：panabee
  • 发布时间：2026/9/9 03:47:06