Machine learning computational model to predict lung cancer using electronic medical records.

Journal: Cancer epidemiology

PMID: 39053365

Abstract

BACKGROUND: Lung cancer (LC) screening using low-dose computed tomography (CT) is recommended according to standard risk criteria or personalized risk calculators. Machine learning (ML) models that can predict disease risk are an emerging method in medicine for identifying hidden associations that are personally unique.

Authors

Matanel Levi

Adelson School of Medicine, Ariel University, Ariel, Israel.
Teddy Lazebnik

Department of Mathematics, Ariel University, Ariel, Israel.
Shiri Kushnir

Research Authority, Rabin Medical Center, Beilinson Campus, Petah-Tiqwa, Israel.
Noga Yosef

Research Unit, Dan, Petah-Tiqwa District, Clalit Health Services Community Division, Ramat-Gan, Israel.
Dekel Shlomi

Adelson School of Medicine, Ariel University, Ariel, Israel; Pulmonary Clinic, Dan, Petah-Tiqwa District, Clalit Health Services Community Division, Ramat-Gan, Israel. Electronic address: dekels1@zahav.net.il.

Keywords

Adult Aged Case-Control Studies Early Detection of Cancer Electronic Health Records Female Humans Lung Neoplasms Machine Learning Male Middle Aged Risk Assessment Risk Factors Smoking Tomography, X-Ray Computed

External Resources

View on PubMed Access via DOI PubMed (39053365)

Machine learning computational model to predict lung cancer using electronic medical records.

Abstract

Authors

Keywords

External Resources

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