Hi everyone,
Mine is a very very basic question. How can we make the Pubmed search results be less in number but accurate at the same time? I have read about the usage of quotes and AND/OR but that doesn't really seem to help. (Maybe I am doing something wrong?) for example: "Kras" and "cancer ". This certainly reduces number of hits as compared to hits I get by just typing KRAS(but still this is a lot and has lot of irrelevant articles). I do not want to type in a specific cancer as I am looking for all cancers in general. I am looking for KRAS gene related treatment options basically.
Does anyone have any documentation on Pubmed search. I remember seeing it on internet once, but not able to locate it again.
Thank you for your time and reply in advance.
To decrease the number of search results and not being more specific at the same time sounds like it is logically, not possible. Have you tried europePMC? Their advanced search seems to have more options than the ncbi pubmed search interface.
follow this video:
https://youtu.be/cw4Om6xSx1g?t=337
Direct from NCBI tutorials. Limit by searching with PubMed.
PubMed for Scientists.
Try the Open Targets Platform. You will see all the results from mining scientific articles from PubMed and PubMed central. The text mining done by EuropePMC and incorporated in our analyses to associated Kras and cancer. In the latest release of the Platform, we have almost 8,000 research articles mined for the co-occurrence of target and disease names (or synonyms) in the same sentence (whether in the title, abstract or body of the paper). So you may want to use our REST API (directly or with the Open Targets Python client) to sieve through this. Just be aware that text mining can give lots of false positives, hence we give a lower score for associations picked up by text mining. More details can be found in our NAR breakthrough paper.
Thank You! This is nice :) will explore more.