A new technology for medical and surgical data organisation: the WSES-WJES Decentralised Knowledge Graph
Year: 2024
Type: article
Abstract: BACKGROUND: The quality of Big Data analysis in medicine and surgery heavily depends on the methods used for clinical data collection, organization, and storage. The Knowledge Graph (KG) represents knowledge through a semantic model, enhancing connections between diverse and complex information. While it can improve the quality of health data collection, it has limitations that can be addressed by the Decentralized (blockchain-powered) Knowledge Graph (DKG). We report our experience in developing a DKG to organize data and knowledge in the field of emergency surgery. METHODS AND RESULTS: The authors leveraged the cyb.ai protocol, a decentralized protocol within the Cosmos network, to develop the Emergency Surgery DKG. They populated the DKG with relevant information using publications from the World Society of Emergency Surgery (WSES) featured in the World Journal of Emergency Surgery (WJES). The result was the Decentralized Knowledge Graph (DKG) for the WSES-WJES bibliography. CONCLUSIONS: Utilizing a DKG enables more effective structuring and organization of medical knowledge. This facilitates a deeper understanding of the interrelationships between various aspects of medicine and surgery, ultimately enhancing the diagnosis and treatment of different diseases. The system's design aims to be inclusive and user-friendly, providing access to high-quality surgical knowledge for healthcare providers worldwide, regardless of their technological capabilities or geographical location. As the DKG evolves, ongoing attention to user feedback, regulatory frameworks, and ethical considerations will be critical to its long-term success and global impact in the surgical field.
Institutions: Gomel State Medical University, Russian Academy of Sciences, Università degli Studi eCampus, Ospedale Infermi di Rimini, Kinshasa General Hospital, Ospedale di Macerata, Azienda Ospedaliera Universitaria Pisana, University of Pavia, Denver Health Medical Center, University of Colorado Denver, Scripps Clinic Medical Group, Ospedale “M. Bufalini” di Cesena
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,790
OpenAlex ID: W4404548035
