Eon uses computational linguistics to identify incidental pulmonary nodules from CT, MR, and X-ray reports

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Eon uses computational linguistics to identify incidental pulmonary nodules from CT, MR, and X-ray reports

Press releases may be edited for formatting or style | October 27, 2020 CT Health IT MRI X-Ray

With Eon's proprietary Computational Linguistics data science model, EPM also extracts clinically relevant findings from radiology reports. The IPN model documents nodule location and characteristics like density, shape, edge, and calcification and automatically populates the information into the EPM dashboard. This allows evidence-based Fleischner Society guidelines to be automatically applied to create an actionable worklist. This approach helps providers by removing excess noise (false positives, low-risk nodules), ensures appropriate patient tracking, and automates complex follow-up.

Schneider adds, "Computational Linguistics is the gold standard for language understanding, in particular for lung nodule identification and characteristics extraction. By embedding evidence, the nodule characteristics focus providers' attention on patients with a high probability of having lung cancer. The high accuracy and reproducibility of our model reduces false positives and does not require radiologists to use a structured report. This approach, along with the embedded risk prediction and automation, should enable providers to prioritize patients and improve their outcomes."

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Eon continues to raise the bar on incidental disease identification and management solutions. The company recently launched a AAA solution, an Actionable Findings module, and is expanding into Pancreas, Thyroid, and Breast in 2021. The company's dedication and drive are fueled by the positive outcomes of early identification and intervention of catastrophic disease.


About Eon
Eon is a Denver-based healthtech company dedicated to revolutionizing the way healthcare data is gathered, curated, and shared among industry professionals. We are on a mission to ensure the right data reaches the right people at the right time to identify disease early and stop it in its tracks. We believe together we can defy disease.


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