Anyone planning a clinical trial is aware of the increasing time and effort it takes to find and recruit patients that meet the criteria. Prescreening has become a significant source of cost and delay, particularly for oncology trials. These problems can be solved through the use of an AI-powered pre-screening tool. To be useful, this tool must:
Extract information from unstructured clinical data
Automatically de-identify patient records
Use an oncology-specific natural language processing (NLP) engine to correctly identify clinical information, even when it is not explicit
Be guided by clinical staff who understand both the use of the tool and oncology clinical practice
Have access to large, heterogeneous clinical data sets
Be easily integrated into hospital contracts, operations, and IT functions
Download the white paper to learn more about the results that can be achieved through an AI-powered pre-screening tool.