To further validate the ability of AI to distinguish COVID-19 from other respiratory diseases, the company also highlighted a new research paper in preprint entitled "Automated triage of COVID-19 from various lung abnormalities using chest CT features". Led by Professor Hayit Greenspan from Tel Aviv University and members of the RADLogics' algorithm development team, the paper studied a fully automated AI-based system that takes as input chest CT scans and triages COVID-19 cases.
The study explored multiple descriptive features, including lung and infections statistics, texture, shape and location, to train a machine learning based classifier that distinguishes between COVID-19 and other lung abnormalities (including community acquired pneumonia). The research evaluated the system on a dataset of 2,191 CT cases and demonstrated a robust outcome with 90.8 percent sensitivity at 85.4 percent specificity with 94.0 percent ROC-AUC. Results of this study are available on arXiv.org, and it has been submitted for review and potential publication.
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RADLogics will be featured this week as part of the RSNA 2020 Imaging AI in Practice demonstration. In addition, RADLogics will be included in the Nuance virtual booth as part of the company's AI Marketplace display.
About RADLogics
RADLogics is a healthcare software company developing AI-Powered solutions that support image analysis to improve radiologists' productivity while enhancing patient outcomes. Based in New York, NY, U.S., and Tel Aviv, Israel, RADLogics is one of the pioneers in using AI & machine learning image analysis and advanced big data analytics to search and analyze imaging data from CTs, MRIs, PET scans, and X-rays to help reduce diagnostics turnaround time from hours to minutes by automating detection and report generation functions. The company's patented AI medical image analysis platform enables rapid development of AI algorithms, and provides seamless integration into existing radiology workflow.
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