Health AI Central
Share:
Peer-Reviewed Publication
PLoS One2020;15(8):e0236021.January 1, 2020Evaluation Study

Using machine learning algorithms to review computed tomography scans and assess risk for cardiovascular disease: Retrospective analysis from the National Lung Screening Trial (NLST).

Amos Stemmer1, Ran Shadmi2, Orna Bregman-Amitai2, David Chettrit2, Denitza Blagev3,4, Mila Orlovsky2, Lisa Deutsch2,5, Eldad Elnekave1,2,6
1Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
2Zebra Medical Vision, Ltd, Shfayim, Israel.
3Pulmonary and Critical Care Division, Intermountain Medical Center, Murray, Utah, United States of America.
4Pulmonary and Critical Care Division, University of Utah, Salt Lake City, Utah, United States of America.
5BioStats Statistical Consulting Ltd, Maccabim, Merkaz Renanim, Israel.
6Department of Diagnostic Radiology, Rabin Medical Center, Beilinson Hospital, Petah Tikva, Israel.
PubMed PMC DOI PDF

Abstract

BACKGROUND: The National Lung Screening Trial (NLST) demonstrated that annual screening with low dose CT in high-risk population was associated with reduction in lung cancer mortality. Nonetheless, the leading cause of mortality in the study was from cardiovascular diseases. PURPOSE: To determine whether the used machine learning automatic algorithms assessing coronary calcium score (CCS), level…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free AccountSign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.