GenomOncology Releases igniteIQ, a Data Extraction Solution
October 29, 2020
CLEVELAND, Oct. 29, 2020 /PRNewswire/ -- GenomOncology announced today the release of their newest product, igniteIQ. igniteIQ is a solution designed to efficiently extract clinically-relevant data from scanned or digital PDF reports, currently NGS and pathology reports, and convert that data to discrete data elements. Through automation and quality assurance, igniteIQ streamlines data validation and analysis to create actionable information.
The igniteIQ solution extracts text from unstructured and semi-structured clinically-relevant documents. Once extracted, the data is then expertly and fastidiously reviewed by in-house, genomic experts, ensuring the highest level of quality assurance. Extracted data elements can then be integrated into existing institutional systems as structured data.
igniteIQ allows clinicians, bioinformaticians, and researchers to dig deeper into historical and current data sets, which is an arduous task with hard copy or scanned documents attached to a medical record or housed in a clinical data warehouse. This extracted data can then be utilized to inform research, improve analytics, and ultimately enhance precision oncology programs.
“With igniteIQ, institutions and labs are able to reduce both the overhead time and cost that is associated with data extraction and transformation. The solution streamlines the data extraction process, giving your team more time to focus on your main priorities, your patients and their treatments,” said Ian Maurer, Chief Technology Officer.
GenomOncology is a genomics software company that develops precision oncology solutions to measurably improve patient therapy and clinical trial options. GenomOncology enables real-time decision support at the point-of-care to accelerate the impact of personalized medicine. Our Precision Oncology Platform supports a large, diverse client base of leading cancer centers and labs by combining world class technology with integrated curated content and annotation sets to enable decision support. Learn more at genomoncology.com.
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