OpenEvidence 8月查询量达 4200 万次，医生日均使用频次超过 Google
源：https://t.co/IX2EQmlaTB
有篇分析挺有意思：美国医生在 OpenEvidence 上一天查 5 次，比 Google 还高频，这种临床需求数据别的公司拿不到。
有人根据 OpenEvidence 8 月 4200 万次查询做了估算：假设 40% 的美国医生是日活用户，按每月约 22 个工作日计算，相当于每位医生每个工作日约 5 次查询。
这个频次高于 Google 的日均 4.2 次搜索和 ChatGPT 的日均 2.
5 次查询。分析认为，这些查询数据暴露了临床实践中的真实信息缺口，OpenEvidence 可以据此更快枚举医生需求，形成数据飞轮。
源：https://t.co/IX2EQmlaTB
源： x.com/lefttailguy/st… illiquid @lefttailguy Rough back of the envelope math: if 40% of US physicians are OpenEvidence DAUs and there's ~22 workdays a month, 42m queries in August implies ~5 queries per workday day per physician (Google is ~4.2 searches per day and ChatGPT is ~2.5 queries per day). This kind of pulse on real-time clinical uncertainty is remarkable. Imagine you could now categorize those queries: see for which flavors of clinical uncertainty existing knowledge / solutions are most scant (or don't exist at all) and then plug in that knowledge / those solutions, fund studies / initiatives to create that knowledge / those solutions, etc. You see how OpenEvidence's flywheel will start to spin a lot faster than the labs in terms of capabilities. It's all about your product enumerating demand in some valuable subset of economic reality faster than competitors. In this case, OpenEvidence enumerates physician demand for information / capabilities that can help solve patient problems. They do this faster and with higher fidelity than anyone else. This is incredibly valuable. 🔗 View Quoted Tweet
本条情报归属 AITOP「行业」核心栏目，重点聚焦北美前沿实验室与硅谷科技巨头。在跨区域产业观察坐标中，该动态直接关联「AI 开发者工具链、Coding Agent 与工程化实践」研究主线，反映出当前技术演进与商业落地的最新风向。涉及核心实体与技术议题包括：OpenEvidence、医疗AI、AI搜索，读者可通过下方标签进入对应专题页查阅历史脉络与关联对比。
信源核验说明：本文原始线索采编自「AI Will」（@FinanceYF5），经 AITOP 多维评分管线结构化提炼。
