Assessing response in endoscopy images of esophageal cancer treated with total neoadjuvant therapy via hybrid-architecture ensemble deep learning

Authors

Ya-Ya Wu
Liang Dai (ORCID: https://orcid.org/0000-0002-4672-6283)
Meichen Liu (ORCID: https://orcid.org/0000-0002-3242-783X)
Yen‐Zhen Lu (ORCID: https://orcid.org/0000-0003-4262-3436)
Peng Yuan (ORCID: https://orcid.org/0000-0001-9906-9275)
Qi Wu (ORCID: https://orcid.org/0009-0001-7744-7906)
Ke-Neng Chen
Hangzhou He (ORCID: https://orcid.org/0009-0009-3050-8773)

Institutions

Peking University (CN)
Peking University Cancer Hospital (CN)
Ministry of Education (ET)

Publication Details

Journal: Frontiers in Oncology
Published: 2025-05-06
DOI: https://doi.org/10.3389/fonc.2025.1590448
Primary Topic: Esophageal Cancer Research and Treatment
Type: article
Field-Weighted Citation Impact: 0.00

Funders

National Natural Science Foundation of China
Peking University
Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support
Beijing Municipal Administration of Hospitals

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article

Assessing response in endoscopy images of esophageal cancer treated with total neoadjuvant therapy via hybrid-architecture ensemble deep learning

Ya-Ya Wu, Liang Dai, Meichen Liu, Yen‐Zhen Lu et al.

May 6, 2025

1 links

Frontiers in Oncology

Esophageal Cancer Research and Treatment

article

Assessing response in endoscopy images of esophageal cancer treated with total neoadjuvant therapy via hybrid-architecture ensemble deep learning

Ya-Ya Wu, Liang Dai, Meichen Liu, Yen‐Zhen Lu, Peng Yuan, Qi Wu, Ke-Neng Chen, Hangzhou He

May 6, 2025article en

Abstract

No abstract available for this paper.

Frontiers in OncologyVol. 15

Peking University (CN), Peking University Cancer Hospital (CN), Ministry of Education (ET)

National Natural Science Foundation of China, Peking University, Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support, Beijing Municipal Administration of Hospitals

Openalex Percentile: Top 83%

Esophageal Cancer Research and Treatment

DOI Open Access PDF OpenAlex

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