Deep Learning Integration of Endoscopic Ultrasound Features and Serum Data Reveals <i>LTB4</i> as a Diagnostic and Therapeutic Target in ESCC
This study demonstrates that deep learning-derived endoscopic ultrasound image features can effectively distinguish ESCC from normal esophageal tissue. By integrating image features with serological data, the authors identified <i>LTB4</i> as a key inflammation-related biomarker with significant diagnostic and therapeutic predictive value.
Authors
- Chunying Bai
- W Zhang
- Yingnan Wang (ORCID: https://orcid.org/0000-0002-0241-6056)
- Jing Qi (ORCID: https://orcid.org/0000-0002-5688-5579)
- S. Huo
- Yang Wang (ORCID: https://orcid.org/0000-0002-5040-2492)
Institutions
- Guilin Medical University (CN)
- Chifeng University (CN)
- Guilin University of Aerospace Technology (CN)
- 181st Hospital of Chinese People's Liberation Army (CN)
- Affiliated Hospital of Guilin Medical College (CN)
- Heinrich Heine University Düsseldorf (DE)
- Jinzhou Medical University (CN)
Publication Details
- Journal
- Cancer Biotherapy and Radiopharmaceuticals
- Published
- 2025-09-18
- DOI
- https://doi.org/10.1177/10849785251380368
- Primary Topic
- Esophageal Cancer Research and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00