The integration of the Internet of Medical Things (IoMT) in gastrointestinal (GI) disease diagnosis from wireless capsule endoscopy (WCE) images introduces both innovative diagnostic capabilities and significant data security challenges. This survey initially focuses on the critical importance of data security in IoMT-based healthcare systems, where the transmission of highly sensitive medical data requires robust encryption, secure communication protocols, and advanced cybersecurity measures to prevent data breaches and ensure patient privacy. It examines various approaches to safeguarding data integrity and secure solutions, which are essential for maintaining trust in IoMT deployments. Furthermore, the survey delves into the classification of GI diseases using WCE images, highlighting the latest advancements in automated diagnostic technologies. These include sophisticated image processing techniques and machine learning algorithms that improve the accuracy and reliability of detecting GI conditions, such as tumors, polyps, and ulcers. By integrating advanced data security measures with cutting-edge classification methods, this survey underscores the dual focus on enhancing diagnostic precision while safeguarding patient information, presenting a holistic approach to future developments in IoMT-based healthcare systems.

gastrointestinal diseases, wireless capsule endoscopy, data security, image classification, data privacy, encryption, healthcare systems, automated diagnosis.