|ECR 2018 / C-2810|
|Multimedia structured reporting employing natural language processing to improve the efficiency of data entry|
Methods and materials
Our initial development of a multimedia structured reporting system, as presented at the ECR 2013, utilized a system of pull-down menus, check boxes and data entry fields to create structured data (figures 1-4) .
The system operated as follows:
- Records key images and voice descriptions that are transcribed to text
- Tags images with metadata referenced to the SNOMED-CT ontology
- Assembles a multimedia report with related information from serial exams arranged in timelines.
During the past year we have integrated an open-source NLP engine (Apache cTAKES) with the structured reporting system to automate the labeling of image findings with metadata that is referenced to the SNOMED-CT ontology . The system labels each finding with its anatomical location, radiologic observation/diagnosis, and secondary descriptors (also known as common data elements) if those elements are contained in the verbal description provided by the radiologist (figures 5-8) .
Thematically related posters
ECR 2018 / C-2352
An electronic system for submitting and reviewing resident schedule requests increases resident satisfaction and residency program administrative efficiency
ECR 2018 / C-2287
Building a Better Data Lake: Enterprise Data Discovery within a Hospital PACS Environment
ECR 2018 / C-2510
Automating the Calculation of Clinical Outcomes with Multimedia Structured Reporting to Satisfy Pay-For-Performance Requirements