A web-based platform for studying the impact of artificial intelligence in video capsule endoscopy

Integrating artificial intelligence (AI) solutions into clinical practice, particularly in the field of video capsule endoscopy (VCE), necessitates the execution of rigorous clinical studies. This work introduces a novel software platform tailored to facilitate the conduct of multi-reader multi-case...

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Bibliographic Details
Published in:	Health informatics journal Vol. 30; no. 4; p. 14604582241296072
Main Authors:	Apostolidis, Georgios, Kakouri, Antigoni, Dimaridis, Ioannis, Vasileiou, Eleni, Gerasimou, Ioannis, Charisis, Vasileios, Hadjidimitriou, Stelios, Lazaridis, Nikolaos, Germanidis, Georgios, Hadjileontiadis, Leontios
Format:	Journal Article
Language:	English
Published:	England 01-10-2024
Subjects:	Artificial Intelligence - trends Capsule Endoscopy - instrumentation Capsule Endoscopy - methods Humans Internet Pilot Projects Software User-Computer Interface video capsule endoscopy system usability scale web application artificial intelligence impact multi–reader multi–case study
Online Access:	Get full text
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Summary:	Integrating artificial intelligence (AI) solutions into clinical practice, particularly in the field of video capsule endoscopy (VCE), necessitates the execution of rigorous clinical studies. This work introduces a novel software platform tailored to facilitate the conduct of multi-reader multi-case clinical studies in VCE. The platform, developed as a web application, prioritizes remote accessibility to accommodate multi-center studies. Notably, considerable attention was devoted to user interface and user experience design elements to ensure a seamless and engaging interface. To evaluate the usability of the platform, a pilot study is conducted. The results indicate a high level of usability and acceptance among users, providing valuable insights into the expectations and preferences of gastroenterologists navigating AI-driven VCE solutions. This research lays a foundation for future advancements in AI integration within clinical VCE practice.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1460-4582 1741-2811 1741-2811
DOI:	10.1177/14604582241296072