Edge Artificial Intelligence Device in Real-Time Endoscopy for Classification of Gastric Neoplasms: Development and Validation Study
Objective: We previously developed artificial intelligence (AI) diagnosis algorithms for predicting the six classes of stomach lesions. However, this required significant computational resources. The incorporation of AI into medical devices has evolved from centralized models to decentralized edge c...
Saved in:
| Main Authors: | Eun Jeong Gong, Chang Seok Bang, Jae Jun Lee |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Biomimetics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-7673/9/12/783 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Edge Artificial Intelligence Device in Real-Time Endoscopy for the Classification of Colonic Neoplasms
by: Eun Jeong Gong, et al.
Published: (2025-06-01) -
The index endoscopic characteristics associated with gastric neoplasms in serial screening of upper gastrointestinal endoscopy
by: Jung Huh, et al.
Published: (2025-07-01) -
Population effectiveness of endoscopy screening for mortality reduction in gastric cancer
by: Naoki Ishii, et al.
Published: (2024-04-01) -
Observation Time for Complete Endoscopy in Gastric Cancer Screening
by: Jae Myung Park
Published: (2018-03-01) -
Validation of Artificial Intelligence Computer-Aided Detection on Gastric Neoplasm in Upper Gastrointestinal Endoscopy
by: Hannah Lee, et al.
Published: (2024-11-01)