Towards Efficient Patient Recruitment for Clinical Trials: Application of a Prompt-Based Learning Model

arXiv:2404.16198v1 Announce Type: new
Abstract: Objective: Clinical trials are essential for advancing pharmaceutical interventions, but they face a bottleneck in selecting eligible participants. Although leveraging electronic health records (EHR) for recruitment has gained popularity, the complex nature of unstructured medical texts presents challenges in efficiently identifying participants. Natural Language Processing (NLP) techniques have emerged as a solution with a recent focus on transformer models. In this study, we aimed to evaluate the performance of a prompt-based large language model for …

abstract application arxiv challenges clinical clinical trials cs.cl ehr electronic electronic health records face health medical nature patient pharmaceutical prompt prompt-based learning records recruitment type unstructured