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With the emergence of online publishing, the number of scientific papers on any topic, e.g. COVID-19, is skyrocketing, while the public press and social media produce data by the second. All this textual data present opportunities to scholars, while simultaneously confronting them with new challenges. Systematic Reviews are “top of the bill” in research, but anyone who has systematically searched literature knows how labor-intensive the process of selecting potentially relevant scientific articles is. To avoid bias in scientific papers, policy and medical guidelines, newspaper articles (etc.) it is of crucial importance to find a way to effectively automatize this screening process. This process involves scanning thousands of studies by hand to find which to include. This is error prone and extremely time intensive, time we may not have in times of crisis! With the rapidly evolving field of Artificial Intelligence (AI) the large amount of manual work can almost completely be replaced by an AI-aided tool.
We do this by making learning algorithms available that interactively query the researcher. This way of interactive training is known as Active Learning. The goal of the tool is to help scholars, medical doctors, journalists, policy makers to get an overview of the most relevant papers for their work as efficiently as possible, while being transparent in the process.
A team of dedicated researchers, engineers, and information specialists are working on the ASReview software. Research and development are very time-consuming. For the nice-to-have features of ASReview, we need your help! You can help not only by developing new features yourself or by improving manuals on Github, but also with a (small or large) financial contribution.