Data-Driven Decision Support for Radiologists: Re-using the National Lung Screening Trial Dataset for Pulmonary Nodule Management-Reference-Cited by-同舟云学术

Data-Driven Decision Support for Radiologists: Re-using the National Lung Screening Trial Dataset for Pulmonary Nodule Management

Published:2014-06-26 Issue:1 Volume:28 Page:18-23
ISSN:0897-1889
Container-title:Journal of Digital Imaging
language:en
Short-container-title:J Digit Imaging

Author:

Morrison James J.,Hostetter Jason,Wang Kenneth,Siegel Eliot L.

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://link.springer.com/content/pdf/10.1007/s10278-014-9720-1.pdf

Reference21 articles.

1. American Cancer Society. Cancer Facts & Figures 2013. Available from: http://www.cancer.org/research/cancerfactsfigures/cancerfactsfigures/cancer-facts-figures 2013. Accessed 14 February 2014.

2. National Cancer Institute. Surveillance, Epidemiology, and End-Results Program. Available from: http://seer.cancer.gov/statfacts/html/lungb.html . Accessed 25 December 2013.

3. Aberle DR, DeMello S, Berg CD, Black WC, Brewer B, Church TR, et al: Results of the two incidence screenings in the national lung screening trial. N Engl J Med 369:920–31, 2013

4. United States Preventative Services Task Force. Lung Cancer Screening 2013 Available from: http://www.uspreventiveservicestaskforce.org/uspstf/uspslung.htm . Accessed 19 December 2013.

5. Tota JE, Ramanakumar AV, Franco EL. Lung cancer screening: review and performance comparison under different risk scenarios. Lung 192:55–63, 2014

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Cross-domain decision making based on TrAdaBoost for diagnosis of breast lesions;Artificial Intelligence Review;2022-09-17

2. Practical Applications of the Internet of Things in Radiation Oncology;Applied Radiation Oncology;2022-09-01

3. Rapid Progress in Intelligent Radiotherapy and Future Implementation;Cancer Investigation;2022-04-03

4. Artificial intelligence in radiology: relevance of collaborative work between radiologists and engineers for building a multidisciplinary team;Clinical Radiology;2021-05

5. A scoping review of clinical decision support tools that generate new knowledge to support decision making in real time;Journal of the American Medical Informatics Association;2020-10-29