Multimodal integration for Barrett’s esophagus
Summary: The esophageal adenocarcinoma is facing a worldwide challenge: early prediction and risk assessment in clinical Barrett’s esophagus (BE). In recent years, the growing interests have been witnessed in prediction and risk assessment in clinical BE. However, the resolution is limited, and the...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-02-01
|
| Series: | iScience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004223025142 |
| _version_ | 1797353576419295232 |
|---|---|
| author | Shubin Liu Shiyu Peng Mengxuan Zhang Ziyuan Wang Lei Li |
| author_facet | Shubin Liu Shiyu Peng Mengxuan Zhang Ziyuan Wang Lei Li |
| author_sort | Shubin Liu |
| collection | DOAJ |
| description | Summary: The esophageal adenocarcinoma is facing a worldwide challenge: early prediction and risk assessment in clinical Barrett’s esophagus (BE). In recent years, the growing interests have been witnessed in prediction and risk assessment in clinical BE. However, the resolution is limited, and the system is huge and expensive for the existing devices. Inspired by the principle of collaboration between human eye vision and brain cortex in data processing, here we propose multimodal learning framework to tackle tasks from various modalities, which can benefit from each other. To our findings, the experimental result indicates that low-level modality can directly affect high-level modality and form the final risk grading based on contribution, which maximizes the clinical performance of medical professionals based on our findings. |
| first_indexed | 2024-03-08T13:33:04Z |
| format | Article |
| id | doaj.art-11fa1461fca0499fad1c38b56263eace |
| institution | Directory Open Access Journal |
| issn | 2589-0042 |
| language | English |
| last_indexed | 2024-03-08T13:33:04Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj.art-11fa1461fca0499fad1c38b56263eace2024-01-17T04:17:12ZengElsevieriScience2589-00422024-02-01272108437Multimodal integration for Barrett’s esophagusShubin Liu0Shiyu Peng1Mengxuan Zhang2Ziyuan Wang3Lei Li4School of Electronics and Information Engineering, Sichuan University, Chengdu 610065, ChinaDepartment of Gastroenterology, First Affiliated Hospital of Shihezi University, Xinjiang 832061, China; Corresponding authorFaculty of Science, The University of Melbourne, Parkville, VIC 3010, AustraliaSchool of Electronics and Information Engineering, Sichuan University, Chengdu 610065, ChinaSchool of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China; Corresponding authorSummary: The esophageal adenocarcinoma is facing a worldwide challenge: early prediction and risk assessment in clinical Barrett’s esophagus (BE). In recent years, the growing interests have been witnessed in prediction and risk assessment in clinical BE. However, the resolution is limited, and the system is huge and expensive for the existing devices. Inspired by the principle of collaboration between human eye vision and brain cortex in data processing, here we propose multimodal learning framework to tackle tasks from various modalities, which can benefit from each other. To our findings, the experimental result indicates that low-level modality can directly affect high-level modality and form the final risk grading based on contribution, which maximizes the clinical performance of medical professionals based on our findings.http://www.sciencedirect.com/science/article/pii/S2589004223025142CancerDiagnosticsHealth sciences |
| spellingShingle | Shubin Liu Shiyu Peng Mengxuan Zhang Ziyuan Wang Lei Li Multimodal integration for Barrett’s esophagus iScience Cancer Diagnostics Health sciences |
| title | Multimodal integration for Barrett’s esophagus |
| title_full | Multimodal integration for Barrett’s esophagus |
| title_fullStr | Multimodal integration for Barrett’s esophagus |
| title_full_unstemmed | Multimodal integration for Barrett’s esophagus |
| title_short | Multimodal integration for Barrett’s esophagus |
| title_sort | multimodal integration for barrett s esophagus |
| topic | Cancer Diagnostics Health sciences |
| url | http://www.sciencedirect.com/science/article/pii/S2589004223025142 |
| work_keys_str_mv | AT shubinliu multimodalintegrationforbarrettsesophagus AT shiyupeng multimodalintegrationforbarrettsesophagus AT mengxuanzhang multimodalintegrationforbarrettsesophagus AT ziyuanwang multimodalintegrationforbarrettsesophagus AT leili multimodalintegrationforbarrettsesophagus |