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.