The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Scoring endoscopic disease activity in IBD: artificial intelligence sees more and better than we do
Open accessAbstract
With great interest we read the review article of Iacucci et al on advanced endoscopic techniques in IBD.1 The authors clearly recognise the current limitations of the different endoscopic scoring tools for disease activity in IBD and provide potential solutions with new advanced techniques. We fully agree that interobserver variability is problematic for treatment planning and IBD drug development and we lack objective definitions of endoscopic remission that predict further disease course in both Crohn’s disease and ulcerative colitis (UC). Scoring systems were mostly developed at the end of the previous century, based on evaluations with fiberoptic endoscopes or poor quality white light video-endoscopes. Intrinsically, it could be anticipated that by seeing more details and nuances such as with virtual chromo-endoscopy, this could result in a superior assessment of the disease activity in IBD. …
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Pursuing greater accuracy through central reading can lead to significant increased costs, prolonged turnaround times, and frustrating delays.
“Furthermore, pursuing greater accuracy through central reading can lead to significant increased costs, prolonged turnaround times, and frustrating delays.72,74”
From Artificial intelligence and endo-histo-omics: new dimensions of precision endoscopy and histology in inflammatory bowel disease (2024) · cites this paper as [74]
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Ozawa, T., Ishihara, S., Fujishiro, M., Saito, H., Kumagai, Y., Shichijo, S., Aoyama, K., & Tada, T. (2018) · Gastrointestinal Endoscopy · doi:10.1016/j.gie.2018.10.020 · Cited by 234
Daperno, M., Comberlato, M., Bossa, F., Biancone, L., Bonanomi, A. G., Cassinotti, A., Cosintino, R., Lombardi, G., Mangiarotti, R., Papa, A., et al. (2014) · Digestive and Liver Disease · doi:10.1016/j.dld.2014.07.010 · Cited by 122
Iacucci, M., Daperno, M., Lazarev, M., Arsenascu, R., Tontini, G. E., Akinola, O., Gui, X. S., Villanacci, V., Goetz, M., Lowerison, M., et al. (2017) · Gastrointestinal Endoscopy · doi:10.1016/j.gie.2017.03.012 · Cited by 92
Self-citationIacucci, M., Furfaro, F., Matsumoto, T., Uraoka, T., Smith, S. C. L., Ghosh, S. K., & Kießlich, R. (2018) · Gut · doi:10.1136/gutjnl-2017-315235 · Cited by 68
Daperno, M., Comberlato, M., Bossa, F., Armuzzi, A., Biancone, L., Bonanomi, A. G., Cosintino, R., Lombardi, G., Mangiarotti, R., Papa, A., et al. (2016) · Journal of Crohn s and Colitis · doi:10.1093/ecco-jcc/jjw181 · Cited by 64
Disagreement Among Gastroenterologists Using the Mayo and Rutgeerts Endoscopic Scores
Fernandes, S. R., Pinto, J. S. L. D., da Costa, P. M., Correia, L., & GEDII (2018) · Inflammatory Bowel Diseases · doi:10.1093/ibd/izx066 · Cited by 40
Dubcenco, E., Zou, G., Stitt, L., Baker, J. P., Jeejeebhoy, K. N., Kandel, G. P., Kim, Y., Grover, S. C., McDonald, J. W., Shackelton, L. M., et al. (2016) · Journal of Crohn s and Colitis · doi:10.1093/ecco-jcc/jjw120 · Cited by 35
Bossuyt, P., Nakase, H., Vermeire, S. A. R. A., et al. (2018) · Gastroenterology · doi:10.1016/s0016-5085(18)30770-4 · Cited by 2
Self-citationZezos, P., Borowski, K., Bajaj, G., et al. (2018) · Gastroenterology · doi:10.1016/s0016-5085(18)30773-x · Cited by 2
Iacucci, M., Lazarev, M. G., Tontini, G. E., et al. (2018) · Gastroenterology · doi:10.1016/s0016-5085(18)31719-0 · Cited by 1
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Big data in IBD: big progress for clinical practice
Seyed Tabib, N. S., Madgwick, M., Sudhakar, P., Verstockt, B., Korcsmaros, T., & Vermeire, S. (2020) · Gut · doi:10.1136/gutjnl-2019-320065 · Cited by 223
Self-citationSutton, R. T., Zai͏̈ane, O. R., Goebel, R., & Baumgart, D. C. (2022) · Scientific Reports · doi:10.1038/s41598-022-06726-2 · Cited by 99
Iacucci, M., Santacroce, G., Zammarchi, I., Maeda, Y., Del Amor, R., Meseguer, P., Kolawole, B. B., Chaudhari, U., Di Sabatino, A., Danese, S., et al. (2024) · The Lancet Gastroenterology & Hepatology · doi:10.1016/s2468-1253(24)00053-0 · Cited by 73
Metadata
- Authors
- Bossuyt, P., Vermeire, S., & Bisschops, R.
- Affiliations
- Universitair Ziekenhuis Leuven (BE)
- Corresponding author
- Bossuyt, Peter
- Venue
- Gut
- Publisher
- BMJ
- Published
- 2019-04-06
- Volume
- 69
- Issue
- 4
- Pages
- 788-789
- ISSN
- 0017-5749 (ISSN-L)
- 1468-3288
- OpenAlex
- W2933820402
- Cited by
- 24
- References
- 10
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 2 · 2023: 3 · 2022: 4 · 2021: 8 · 2020: 3 · 2019: 1
- Type
- journal article
- Language
- en
- Open access
- green
- lirias.kuleuven.be
- Licence
- other-oa
- Locations
- Gut (publishedVersion)
- PubMed (publishedVersion)
- Lirias (KU Leuven) (submittedVersion, other-oa)
- HighWire Press Open Archive (submittedVersion)
- Topics
- Health Sciences › Medicine › Gastroenterology › Inflammatory Bowel Disease
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
- Keywords
- inflammatory bowel disease, endoscopic activity, artificial intelligence, disease activity assessment, endoscopy, computer-aided diagnosis
- MeSH terms
- Artificial Intelligence, Colitis, Ulcerative, Endoscopy, Humans, Inflammatory Bowel Diseases
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