Implementing machine learning to predict survival outcomes in patients with resected pulmonary large cell neuroendocrine carcinoma.

Journal: Expert review of anticancer therapy

PMID: 39242355

Abstract

BACKGROUND: The post-surgical prognosis for Pulmonary Large Cell Neuroendocrine Carcinoma (PLCNEC) patients remains largely unexplored. Developing a precise prognostic model is vital to assist clinicians in patient counseling and creating effective treatment strategies.

Authors

Min Liang

Department of Respiratory and Critical Care Medicine, Maoming People's Hospital, Maoming, China.
Shantanu Singh

Imaging Platform, Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA.
Jian Huang

Center for Informational Biology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, P. R. China.

Keywords

Adult Aged Carcinoma, Large Cell Carcinoma, Neuroendocrine Cohort Studies Female Humans Lung Neoplasms Machine Learning Male Middle Aged Prognosis Retrospective Studies SEER Program Survival Rate

External Resources

View on PubMed Access via DOI PubMed (39242355)

Implementing machine learning to predict survival outcomes in patients with resected pulmonary large cell neuroendocrine carcinoma.

Abstract

Authors

Keywords

External Resources

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