Systematic Review Literature Search

Systematic review literature searches aim to efficiently and comprehensively identify relevant studies for a research question, a crucial step in evidence-based research. Current research focuses on improving search strategies, particularly through automated methods like AI-powered Boolean query generation and neural ranking algorithms (e.g., BERT-based models) to prioritize relevant documents and suggest appropriate MeSH terms. These advancements aim to reduce the time and effort required for conducting systematic reviews, ultimately enhancing the quality and efficiency of scientific research across various fields, including medicine and engineering.