News | Artificial Intelligence | May 20, 2019

AI Detects Unsuspected Lung Cancer in Radiology Reports, Augments Clinical Follow-up

Research study demonstrates healthcare artificial intelligence application to detect and triage pulmonary nodules

AI Detects Unsuspected Lung Cancer in Radiology Reports, Augments Clinical Follow-up

May 20, 2019 — Digital Reasoning 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 percent. The findings have now been published in the Journal of Clinical Oncology as part of the 2019 American Society of Clinical Oncology (ASCO) meeting proceedings.1

For health systems, reviewing incidental findings can be a time and labor intensive process.2 Other studies show the rate for timely clinical follow-up can fall as low as 29 percent across the industry.3 Applying advanced artificial intelligence (AI) to radiology reports to automate the identification and triage of pulmonary nodules, empowers doctors to focus on reviewing and acting on the most high-risk cases. This results in improved patient safety and faster time-to-treatment without excess labor.

During the research study, Digital Reasoning analyzed 8,879 free-text, narrative computed tomography (CT) 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: www.ascopubs.org/journal/jco

References

1. French C., Makowski M., Terker S., et al. Automating incidental findings in radiology reports using natural language processing and machine learning to identify and classify pulmonary nodules. Presented at ASCO 2019. J Clin Oncol 37, 2019 (suppl; abstr e18093)

2. Rosenkrantz A.B., Xue X., Gyftopoulos S., et al. Downstream Costs Associated with Incidental Pulmonary Nodules Detected on CT. Acad Radiol., published online Aug. 6, 2018. pii: S1076-6332(18)30372-6, 2018

3. Blagev D.P., Lloyd J.F., Conner K., et al. Follow-up of Incidental Pulmonary Nodules and the Radiology Report. J Am Coll Radiol., published online Dec. 6, 2013. 13(2 Suppl):R18-24, 2016

Related Content

ADHD Medication May Affect Brain Development in Children

Images of regions of interest (colored lines) in the white matter skeleton representation. Data from left and right anterior thalamic radiation (ATR) were averaged. Image courtesy of C. Bouziane et al.

News | Neuro Imaging | August 16, 2019
A drug used to treat attention-deficit/hyperactivity disorder (ADHD) appears to affect development of the brain’s...
First Patient Enrolled in World's Largest Brain Cancer Clinical Trial
News | Radiation Therapy | August 15, 2019
Henry Ford Cancer Institute is first-in-the-world to enroll a glioblastoma patient in the GBM AGILE Trial (Adaptive...
Efficacy of Isoray's Cesium Blu Showcased in Recent Studies
News | Brachytherapy Systems | August 14, 2019
August 14, 2019 — Isoray announced a trio of studies recently reported at scientific meetings and published in medica
Imago Systems Announces Collaboration With Mayo Clinic for Breast Imaging

Image courtesy of Imago Systems

News | Mammography | August 14, 2019
Image visualization company Imago Systems announced it has signed a know-how license with Mayo Clinic. The multi-year...
Artificial Intelligence Could Yield More Accurate Breast Cancer Diagnoses
News | Artificial Intelligence | August 13, 2019
University of California Los Angeles (UCLA) researchers have developed an artificial intelligence (AI) system that...
The CT scanner might not come with protocols that are adequate for each hospital situation, so at Phoenix Children’s Hospital they designed their own protocols, said Dianna Bardo, M.D., director of body MR and co-director of the 3D Innovation Lab at Phoenix Children’s.

The CT scanner might not come with protocols that are adequate for each hospital situation, so at Phoenix Children’s Hospital they designed their own protocols, said Dianna Bardo, M.D., director of body MR and co-director of the 3D Innovation Lab at Phoenix Children’s.

Sponsored Content | Case Study | Radiation Dose Management | August 13, 2019
Radiation dose management is central to child patient safety. Medical imaging plays an increasing role in the accurate...
Half of Hospital Decision Makers Plan to Invest in AI by 2021
News | Artificial Intelligence | August 08, 2019
August 8, 2019 — A recent study conducted by Olive AI explores how hospital leaders are responding to the imperative
Videos | CT Angiography (CTA) | August 07, 2019
This is a quick walk around of the new Siemens Somatom Go.top cardiovascular edition compact computed tomography (CT)
Videos | CT Angiography (CTA) | August 07, 2019
This is a quick walk around of the GE Healthcare Cardiographe dedicated cardiac CT system on display at the...