Back to search

Article

Development of a Diagnostic Model for Barrett's Esophagus and Esophageal Adenocarcinoma Based on Machine Learning and Immune Infiltration

2025-12-03

Abstract excerpt

<title>Abstract</title> <p>Background Esophageal adenocarcinoma (EAC) is a highly lethal cancer, with Barrett's esophagus (BE) as its only known precursor. Early diagnosis is challenging, and the key biomarkers and mechanisms driving the BE-to-EAC progression are not fully understood. Methods We integrated transcriptomic data from BE (from the Gene Expression Omnibus (GEO)) and EAC (from The Cancer Genome Atlas (...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
289c4a05-6b42-5760-a171-ae88332380f0
DOI
10.21203/rs.3.rs-8004374/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Development of a Diagnostic Model for Barrett's Esophagus and Esophageal Adenocarcinoma Based on Machine Learning and Immune InfiltrationDOI 10.21203/rs.3.rs-8004374/v1
Select a neighboring publication to make it the new centre.