I have a naive question for you all. I want to know where to learn the following task I am trying to do. So if anyone has a suggestion and points me in the right direction, it is very much appreciated.
I search and collect hundreds of articles every week in PubMed based on keywords. However, there are many other complex factors involved in choosing what I consider relevant articles. This can be for example simply reading the title and abstract to understand the context and this could not be captured by just keywords. I usually end up discarding more than 80% of the articles collected.
So I wonder if I can implement a machine learning workflow and use the thousands of articles I hand-picked in the past as ‘relevant articles’ and train the machine learning workflow to filter the new set of articles I collected in PubMed.
Is this first of all possible? and if yes, can anyone give me a hint/guidance on how I can learn and implement such a workflow?
Thanks all in advance for your support.