Evaluating Chemical-Gene-Disease Text-Mining
Protocol cited in 3 other protocols
Variable analysis
- Manipulated by researchers to evaluate the performance of prototype text-mining applications
- The performance of prototype text-mining applications
- Approximately 1,600 journal articles previously manually curated for CTD, which were used as a baseline data set, or 'gold standard', to evaluate the performance of the prototype text-mining applications
- The 1,600 documents contained 6,664 curated actors, including chemicals, genes, and diseases and represented data for 10 different priority chemicals: urethane, aspartame, 2-acetylaminofluorene, cyclophosphamide, indomethacin, aniline, raloxifene, amsacrine, phenacetin, and doxorubicin
Annotations
Based on most similar protocols
As authors may omit details in methods from publication, our AI will look for missing critical information across the 5 most similar protocols.
About PubCompare
Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.
We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.
However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.
Ready to get started?
Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required
Revolutionizing how scientists
search and build protocols!