Cargando…
Conceptual Framework and Documentation Standards of Cystoscopic Media Content for Artificial Intelligence
BACKGROUND: The clinical documentation of cystoscopy includes visual and textual materials. However, the secondary use of visual cystoscopic data for educational and research purposes remains limited due to inefficient data management in routine clinical practice. METHODS: A conceptual framework was...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cornell University
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9882574/ https://www.ncbi.nlm.nih.gov/pubmed/36713258 |
_version_ | 1784879320611684352 |
---|---|
author | Eminaga, Okyaz Lee, Timothy Jiyong Ge, Jessie Shkolyar, Eugene Laurie, Mark Long, Jin Hockman, Lukas Graham Liao, Joseph C. |
author_facet | Eminaga, Okyaz Lee, Timothy Jiyong Ge, Jessie Shkolyar, Eugene Laurie, Mark Long, Jin Hockman, Lukas Graham Liao, Joseph C. |
author_sort | Eminaga, Okyaz |
collection | PubMed |
description | BACKGROUND: The clinical documentation of cystoscopy includes visual and textual materials. However, the secondary use of visual cystoscopic data for educational and research purposes remains limited due to inefficient data management in routine clinical practice. METHODS: A conceptual framework was designed to document cystoscopy in a standardized manner with three major sections: data management, annotation management, and utilization management. A Swiss-cheese model was proposed for quality control and root cause analyses. We defined the infrastructure required to implement the framework with respect to FAIR (findable, accessible, interoperable, reusable) principles. We applied two scenarios exemplifying data sharing for research and educational projects to ensure the compliance with FAIR principles. RESULTS: The framework was successfully implemented while following FAIR principles. The cystoscopy atlas produced from the framework could be presented in an educational web portal; a total of 68 full-length qualitative videos and corresponding annotation data were sharable for artificial intelligence projects covering frame classification and segmentation problems at case, lesion and frame levels. CONCLUSION: Our study shows that the proposed framework facilitates the storage of the visual documentation in a standardized manner and enables FAIR data for education and artificial intelligence research. |
format | Online Article Text |
id | pubmed-9882574 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cornell University |
record_format | MEDLINE/PubMed |
spelling | pubmed-98825742023-01-28 Conceptual Framework and Documentation Standards of Cystoscopic Media Content for Artificial Intelligence Eminaga, Okyaz Lee, Timothy Jiyong Ge, Jessie Shkolyar, Eugene Laurie, Mark Long, Jin Hockman, Lukas Graham Liao, Joseph C. ArXiv Article BACKGROUND: The clinical documentation of cystoscopy includes visual and textual materials. However, the secondary use of visual cystoscopic data for educational and research purposes remains limited due to inefficient data management in routine clinical practice. METHODS: A conceptual framework was designed to document cystoscopy in a standardized manner with three major sections: data management, annotation management, and utilization management. A Swiss-cheese model was proposed for quality control and root cause analyses. We defined the infrastructure required to implement the framework with respect to FAIR (findable, accessible, interoperable, reusable) principles. We applied two scenarios exemplifying data sharing for research and educational projects to ensure the compliance with FAIR principles. RESULTS: The framework was successfully implemented while following FAIR principles. The cystoscopy atlas produced from the framework could be presented in an educational web portal; a total of 68 full-length qualitative videos and corresponding annotation data were sharable for artificial intelligence projects covering frame classification and segmentation problems at case, lesion and frame levels. CONCLUSION: Our study shows that the proposed framework facilitates the storage of the visual documentation in a standardized manner and enables FAIR data for education and artificial intelligence research. Cornell University 2023-01-18 /pmc/articles/PMC9882574/ /pubmed/36713258 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Eminaga, Okyaz Lee, Timothy Jiyong Ge, Jessie Shkolyar, Eugene Laurie, Mark Long, Jin Hockman, Lukas Graham Liao, Joseph C. Conceptual Framework and Documentation Standards of Cystoscopic Media Content for Artificial Intelligence |
title | Conceptual Framework and Documentation Standards of Cystoscopic Media Content for Artificial Intelligence |
title_full | Conceptual Framework and Documentation Standards of Cystoscopic Media Content for Artificial Intelligence |
title_fullStr | Conceptual Framework and Documentation Standards of Cystoscopic Media Content for Artificial Intelligence |
title_full_unstemmed | Conceptual Framework and Documentation Standards of Cystoscopic Media Content for Artificial Intelligence |
title_short | Conceptual Framework and Documentation Standards of Cystoscopic Media Content for Artificial Intelligence |
title_sort | conceptual framework and documentation standards of cystoscopic media content for artificial intelligence |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9882574/ https://www.ncbi.nlm.nih.gov/pubmed/36713258 |
work_keys_str_mv | AT eminagaokyaz conceptualframeworkanddocumentationstandardsofcystoscopicmediacontentforartificialintelligence AT leetimothyjiyong conceptualframeworkanddocumentationstandardsofcystoscopicmediacontentforartificialintelligence AT gejessie conceptualframeworkanddocumentationstandardsofcystoscopicmediacontentforartificialintelligence AT shkolyareugene conceptualframeworkanddocumentationstandardsofcystoscopicmediacontentforartificialintelligence AT lauriemark conceptualframeworkanddocumentationstandardsofcystoscopicmediacontentforartificialintelligence AT longjin conceptualframeworkanddocumentationstandardsofcystoscopicmediacontentforartificialintelligence AT hockmanlukasgraham conceptualframeworkanddocumentationstandardsofcystoscopicmediacontentforartificialintelligence AT liaojosephc conceptualframeworkanddocumentationstandardsofcystoscopicmediacontentforartificialintelligence |