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Article

Prediction of p53 mutation status in rectal cancer patients based on magnetic resonance imaging-based nomogram: a study of machine learning.

Cancer imaging : the official publication of the International Cancer Imaging Society - 18 Sept 2023

Zhong Xia, Peng Jiaxuan, Shu Zhenyu, Song Qiaowei, Li Dongxue

Abstract excerpt

BACKGROUND: The current study aimed to construct and validate a magnetic resonance imaging (MRI)-based radiomics nomogram to predict tumor protein p53 gene status in rectal cancer patients using machine learning. METHODS: Clinical and imaging data from 300 rectal cancer patients who underwent radical resections were included in this study, and a total of 166 patients with p53 mutations according to pathology...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 37723592
DOI: 10.1186/s40644-023-00607-1
PMCID: PMC10507842

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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