20.500.12556/DiRROS-27841 Artificial intelligence to revolutionize IBD clinical trials a comprehensive review Integrating artificial intelligence (AI) into clinical trials for inflammatory bowel disease (IBD) has potential to be transformative to the field. This article explores how AIdriven technologies, including machine learning (ML), natural language processing, and predictive analytics, have the potential to enhance important aspects of IBD trials—from patient recruitment and trial design to data analysis and personalized treatment strategies. As AI advances, it has potential to improve long-standing challenges in trial efficiency, accuracy, and personalization with the goal of accelerating the discovery of novel therapies and improve outcomes for people living with IBD. AI can streamline multiple trial phases, from target identification and patient recruitment to data analysis and monitoring. By integrating multiomics data, electronic health records, and imaging repositories, AI can uncover molecular targets and personalize trial strategies, ultimately expediting drug development. However, the adoption of AI in IBD clinical trials encounters significant challenges. These include technical barriers in data integration, ethical concerns regarding patient privacy, and regulatory issues related to AI validation standards. Additionally, AI models risk producing biased outcomes if training datasets lack diversity, potentially impacting underrepresented populations in clinical trials. Addressing these limitations requires standardized data formats, interdisciplinary collaboration, and robust ethical frameworks to ensure inclusivity and accuracy. Continued partnerships among clinicians, researchers, data scientists, and regulators will be essential to establish transparent, patient-centered AI frameworks. By overcoming these obstacles, AI has the potential to enhance the efficiency, equity, and efficacy of IBD clinical trials, ultimately benefiting patient care AI artificial intelligence clinical trials true false true Angleški jezik Ni določen Neznano 2026-02-26 11:04:28 2026-02-26 11:04:29 2026-02-27 03:58:35 0000-00-00 00:00:00 2025 0 0 Nasl. z nasl. zaslona; Opis vira z dne 26. 2. 2025; str. 1-20 Vol. 18 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 61 1756-2848 10.1177/17562848251321915 227469827 RAZ_Sedano_Rocio_2025.pdf RAZ_Sedano_Rocio_2025.pdf 1 CDD9307DF03AD2F6F43913118190E2D1 7c56d91db97eab4e8bcf8e08cdbed782514aff2251529ce8cb350f45a27b19c6 cf402174-12fa-11f1-9cb0-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=40965 https://journals.sagepub.com/doi/10.1177/17562848251321915 1 8a827883-12fa-11f1-9cb0-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=40964 Univerzitetni klinični center Ljubljana 0 0 0