Analysis of articles through dictionaries (AMI)
This is a notebook for retrieving papers on Obesity and analysing them. The strategy is:
- query PubMed or EuropePMC for "obesity"
- apply obesity-relevant dictionaries
This will use the OpenAccess literature only and will be a subset. The main emphasis is to show how different types of article can be filtered in or out using dictionaries.
This is a collaboration with our long-standing collaborators James Thomas and colleagues at UCL-EPPI. This notebook will feature the development of the ContentMine tools, and how they can interoperate with the UCL tools.
We use 2 sources:
UCL. This tool (in beta) queries PubMed and retrieves metadata and abstracts. It then applies machine learning to add facets for specific topics (in this case RCT (did the article report a Randomised Controlled Trial) and Human (were human subjects an important part of the reported work)).
ContentMine . We use getpapers to search EuropePMC for "obesity" , retrieve a subset (ca 500) papers and apply word frequencies and dictionaries:
Each tool (UCL and CM) reports results as a dashboard, with a row for each article.