Machine learning-based reconstruction of prognostic staging for gastric cancer patients with different differentiation grades: A multicenter retrospective study.

Journal: World journal of gastroenterology

PMID: 40248057

Abstract

BACKGROUND: The prognosis of gastric cancer (GC) patients is poor, and an accurate prognostic staging system would help assess patients' prognostic status before treatment and determine appropriate treatment strategies.

Authors

Yong-Le Zhang

Department of Gastrointestinal Surgery, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China.
Hai-Bin Song

Department of Gastrointestinal Surgery, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China.
Ying-Wei Xue

Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China. xueyingwei@hrbmu.edu.cn.

Keywords

Adult Aged Female Humans Lymph Nodes Lymphatic Metastasis Machine Learning Male Middle Aged Neoplasm Grading Neoplasm Staging Predictive Value of Tests Prognosis Retrospective Studies SEER Program Stomach Neoplasms

External Resources

View on PubMed Access via DOI PubMed (40248057)

Machine learning-based reconstruction of prognostic staging for gastric cancer patients with different differentiation grades: A multicenter retrospective study.

Abstract

Authors

Keywords

External Resources

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