Digital Reasoning's AI Analytics Detects Unsuspected Lung Cancer in Radiology Reports and Augments Clinical Follow-Up

NASHVILLE, Tenn., May 16, 2019 (GLOBE NEWSWIRE) -- Digital Reasoning, a leader in Artificial Intelligence (AI) that understands human intentions and behaviors, today announced results from its automated radiology report analytics research. In a series of experiments on radiology reports from Emergency Departments, Inpatient and Outpatient healthcare facilities, Digital Reasoning used natural language processing (NLP) and machine learning (ML) to identify and triage high-risk lung nodules, achieving queue precision of 90.2%. The findings have now been published in the Journal of Clinical Oncology as part of the 2019 ASCO meeting proceedings.

“In the complex world of healthcare, new technologies like AI create opportunities to simplify processes and improve patient care,” said Chris Cashwell, Vice President of healthcare solutions at Digital Reasoning. “Our work emphasizes the real-world impact of automating the analysis of radiology reports – allowing doctors to spend less time reviewing documents and more time providing world-class care for their patients.”

For health systems, reviewing incidental findings can be a time and labor intensive process.¹ Other studies show the rate for timely clinical follow-up can fall as low as 29% across the industry.² Applying advanced AI to radiology reports to automate the identification and triage of pulmonary nodules, empowers doctors to focus on reviewing and acting on the most hgh risk cases resulting in improved patient safety and faster time-to-treatment without excess labor.

During the research study, Digital Reasoning analyzed 8,879 free-text, narrative computerized tomography radiology reports from Dec. 8, 2015 through April 23, 2017.  Today, those analytics are embedded in an enterprise solution utilized across more than 150 hospitals and 60 cancer centers in the United States. 

For more information, please find Digital Reasoning’s paper in the Journal of Clinical Oncology here: http://abstracts.asco.org/239/AbstView_239_270165.html

References

1. Rosenkrantz AB, Xue X, Gyftopoulos S, Kim DC, Nicola GN. Downstream Costs Associated with Incidental Pulmonary Nodules Detected on CT.  Acad Radiol pii: S1076-6332(18)30372-6, 2018

2. Blagev DP, Lloyd JF, Conner K, Dickerson J, Adams D, Stevens SM, Woller SC, Evans RS, Elliott CG.  Follow-up of Incidental Pulmonary Nodules and the Radiology Report. Follow-up of Incidental Pulmonary Nodules and the Radiology Report.   J Am Coll Radiol 13(2 Suppl):R18-24, 2016

Media Contacts
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About American Society of Clinical Oncology (ASCO) Conference
Founded in 1964, ASCO is the world’s leading professional organization for physicians, oncology professionals, and research scientists in the field of oncology. ASCO’s Mission over the years has been to conquer cancer through research, education, and promotion of the highest quality patient care.

ASCO’s Annual meeting represents the world’s largest gathering of oncology physicians, biotechnology executives, researchers, patient advocates, and investment analysts to discuss cutting-edge clinical research and therapeutics in oncology, and to gain insights for improving cancer care.

For additional information on the 2019 ASCO’s Annual meeting, please visit https://www.asco.org/.

About Digital Reasoning
Digital Reasoning is a global leader in artificial intelligence that understands human intentions and behaviors. Our award-winning AI platform automates key tasks and uncovers transformative insights across vast amounts of human communications for many of the world’s leading organizations and government agencies. For more information go to www.digitalreasoning.com and follow on Twitter at @dreasoning.

A photo accompanying this announcement is available at //www.globenewswire.com/NewsRoom/AttachmentNg/b4efca10-260c-4783-91af-4f387d9289ae

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