A Support Vector Machine Model Predicting the Risk of Duodenal Cancer in Patients with Familial Adenomatous Polyposis at the Transcript Levels.

Journal: BioMed research international

PMID: 32626748

Abstract

OBJECTIVE: Familial adenomatous polyposis (FAP) is one major type of inherited duodenal cancer. The estimate of duodenal cancer risk in patients with FAP is critical for selecting the optimal treatment strategy.

Authors

Weiqing Liu

Department of Internal Medicine Oncology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Jian Dong
Shumin Ma

Department of Oncology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Lei Liang

Department of Oncology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Jun Yang

Cardiovascular Endocrinology Laboratory, Hudson Institute of Medical Research, Clayton, Victoria, Australia; Department of Medicine, Monash University, Clayton, Victoria, Australia.

Keywords

Adenomatous Polyposis Coli Computational Biology Databases, Genetic Duodenal Neoplasms Humans Metabolic Networks and Pathways Risk Assessment Support Vector Machine Transcriptome

External Resources

View on PubMed Access via DOI PubMed (32626748)

A Support Vector Machine Model Predicting the Risk of Duodenal Cancer in Patients with Familial Adenomatous Polyposis at the Transcript Levels.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals