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When I was in grad school, I joined a startup incubator and build a prototype which combined two of the tools mentioned in the article: "a query builder (by dem
by i000 5y ago
When I was in grad school, I joined a startup incubator and build a prototype which combined two of the tools mentioned in the article: "a query builder (by demonstration)" and "A paper recommender system", a simple companion which would help scientist to not miss relevant research to them. This was 10 years ago, before Google Scholar has similar features.
The incubator introduced me to advisors with business experience in this field. And I got told in no uncertain terms what is the gist of this article: The value lies in the molecular and clinical data. In 2021 I would add digital pathology / imaging data.
- geoduck14 5y ago>And I got told in no uncertain terms what is the gist of this article: The value lies in the molecular and clinical data. In 2021 I would add digital pathology / imaging data. I feel like you are trying to tell me something REALLY valuable, but I don't quite understand it. Can you please elaborate?
- potatoman22 5y agoMy take: answering questions using clinical data > answering questions with papers
- i000 5y agoThere is immense value in clinical data (all the information captured and siloed through EHR). Pharma companies pay for access to it to gather real-world evidence (RWE) how, for example, their drug performs. Molecular information is increasingly valuable too for research, biomarker development, patient cohort identification etc. The imaging data and pathology data are valuable because they are typically expertly annotated and can be used to train computer-vision algorithms etc. to solve medical problems - like diagnosis.