Challenges and Solutions of Machine Learning in Systematic Review Study Selection
Systematic reviews (SRs) are the cornerstone of evidence-based medicine, meticulously synthesizing vast research to inform healthcare decisions. However, the ever-growing volume of scientific literature poses a formidable challenge to researchers undertaking these reviews. Enter machine learning (ML), a powerful tool with the potential to revolutionize study selection in SRs, streamlining the process and potentially reducing bias.
However, like any emerging technology, implementing ML in SRs comes with its own challenges. Let's delve into some of the key hurdles and explore potential solutions: