Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
DOP096 ChatIBD: AI Companion for Inflammatory Bowel Disease (IBD) Clinicians
0
Zitationen
3
Autoren
2026
Jahr
Abstract
Abstract Background Inflammatory bowel disease (IBD), including Crohn’s disease and ulcerative colitis, is a growing global health challenge. Managing IBD is increasingly complex, with rapidly evolving treatment options, proliferating guidelines, and varying regional practices. Clinicians face limited time to remain current, and access to IBD expertise is uneven worldwide. Methods ChatIBD (www.chatibd.com) is a new artificial intelligence (AI) tool, designed by IBD clinicians, to support healthcare professionals delivering IBD care. By combining retrieval-augmented generation with curated guidelines (>30 guidelines from ECCO, BSG, AGA, ACG, ESPGHAN), ChatIBD provides clear, evidence-based answers to practical clinical questions, always referenced to trusted sources and tailored to the user’s region. A “deep research” mode extends searches to emerging literature, ensuring clinicians can keep pace with innovation. Safety and accuracy are reinforced through an integrated dosing database built from European Medicines Agency (EMA) product information, delivering regulator-approved induction and maintenance regimens. ChatIBD’s multilingual capability (English and Spanish in testing) extends accessibility across diverse settings. ChatIBD query handling architecture is shown in Figure 1. Results ChatIBD launched in October 2025. Since going live, a total of 2,642 queries, in 19 different languages were submitted from 578 registered users residing in 54 different countries. The top 5 countries were UK (n = 617 queries), Spain (n = 362 queries), USA (n = 270 queries), Brazil (n = 182 queries) and Germany (n = 119 queries), respectively. Top 5 languages were English (70.1%), Spanish (15.4%), Portuguese (6.3%), German (3.7%) and Dutch (2.7%), respectively. The domains and intent of clinical queries are shown in Table 1. In the current beta testing phase, ChatIBD has demonstrated >95% accuracy across 400 reviewed responses. Conclusion By making specialist-level knowledge accessible, ChatIBD has the potential to reduce unwarranted variation in care, empower clinicians, and support better outcomes for people with IBD - while offering a scalable digital health model that can extend to other disease areas/specialties. Multilingual, global access also helps democratise access to information worldwide especially in developing countries where we are seeing a rapid increase in the incidence and prevalence of IBD. Conflict of interest: Gros, Beatriz: Beatriz Gros has served as a speaker for Abbvie, Johnson and Johnson, Takeda, Roche, Gilead, Pfizer and Galapagos and has served as an advisor for Roche, Gilead, Abbvie, Galapagos and Takeda Plevris, Nikolas: No conflict of interest Chuah, Cher Shiong: No conflict of interest
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.214 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.071 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.429 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.418 Zit.