In Black Box We Trust: Machine Learning-Based Record Screening for Systematic Reviews
I had an amazing two days at Search Solutions 2022 with a lot of lively discussions, and thrown, hit and missed punches :D I don’t miss Search Solutions, the only conference I attend every year.
I’m not going to keep you waiting, I’m going straight to the point. It is time for us to start trusting machine learning-based features for searching and screening stages of systematic reviews. Believe it or not, we will have no choice but to gradually adopt them into our routine workload or fall behind our fellow colleagues.
Using devices and technologies that use Machine Learning (ML) features in daily life and work is inevitable. Sometimes you have a choice to use or not to use them (turn off your smartphone), and sometimes you don’t (your bank’s chatbot until you get mad, then it connects you to a human).
If you are conducting a systematic review, you have a choice to use or not use ML-based technologies. Before writing this post, I have spoken to many of my colleagues who are big fans of automation, but it does not necessarily mean that they like or use ML-based features!
What is the Difference Between Automation and ML?
Automation of course differs from ML. In…
