Screening Process

Screening processes, encompassing the selection of candidates from a larger pool based on predefined criteria, are a crucial aspect of many fields, aiming to optimize efficiency and fairness while maximizing the selection of qualified individuals. Current research focuses on improving screening methods through algorithmic advancements, such as incorporating large language models (LLMs) for automated text analysis and developing novel optimization algorithms to enhance efficiency and mitigate biases introduced by sequential screening or initial ordering effects. These improvements have significant implications for various applications, including systematic reviews, hiring processes, medical diagnostics, and resource allocation in public health initiatives, ultimately leading to more effective and equitable decision-making.