Socio-Economic Factors and Clinical Context Can Predict Adherence to Incidental Pulmonary Nodule Follow-up via Machine Learning Models.

Journal: Journal of the American College of Radiology : JACR

PMID: 38461910

Abstract

OBJECTIVE: To quantify the relative importance of demographic, contextual, socio-economic, and nodule-related factors that influence patient adherence to incidental pulmonary nodule (IPN) follow-up visits and evaluate the predictive performance of machine learning models utilizing these features.

Authors

Zhuoyang Wang

Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Eduardo J Mortani Barbosa

Department of Bioengineering, School of Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address: Eduardo.Barbosa@pennmedicine.upenn.edu.

Keywords

Adult Aged Female Humans Incidental Findings Lung Neoplasms Machine Learning Male Middle Aged Patient Compliance Socioeconomic Factors Solitary Pulmonary Nodule

External Resources

View on PubMed Access via DOI PubMed (38461910)

Socio-Economic Factors and Clinical Context Can Predict Adherence to Incidental Pulmonary Nodule Follow-up via Machine Learning Models.

Abstract

Authors

Keywords

External Resources

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