Can AI tools help me find the latest research results in the literature review?

AI tools significantly facilitate the discovery of the latest research results during literature reviews. They automate the scanning of vast academic databases and preprint servers with far greater speed and comprehensiveness than manual searching. These tools leverage algorithms to continuously monitor scholarly publications, often employing natural language processing to identify relevant studies based on user-defined keywords, topics, or saved queries. Key principles include automated alerting systems (e.g., email/RSS feeds), personalized recommendations, and citation network analysis to track emerging works. Necessary conditions include reliable API access to databases and robust search filters. However, coverage depends on the specific tool's indexed sources, critical evaluation remains essential due to potential algorithm bias or preprint inclusion, and relevance filtering requires initial user calibration. To implement this, researchers first select specialized tools (e.g., Semantic Scholar, Dimensions, Elicit, Scopus Alerts) and configure searches with precise keywords and filters. Second, they establish automated alerts to receive notifications of new publications meeting their criteria. Third, they regularly review these curated results, critically assessing relevance and quality, before integrating pertinent findings into their review. This systematic approach enhances comprehensiveness and timeliness.