Scholarlink

<p>Artificial intelligence (AI) is rapidly transforming the management landscape of inflammatory bowel disease (IBD). While early applications in endoscopy, digital pathology and cross-sectional imaging drew substantial attention, next-generation AI systems that enable deeper disease understanding, personalized treatment and streamlined clinical workflows are now emerging. These advances encompass the multimodal integration of endoscopic, histological and molecular data (‘endo-histo-omics’); AI-assisted assessment of the intestinal barrier; remote monitoring via wearables; and the incorporation of large language models for decision-making support and patient interactions. This Perspective traces the evolution of AI in IBD from domain-specific tools to foundational platforms supporting data-driven precision medicine. We highlight validated AI applications across diagnosis, monitoring, outcome prediction and neoplasia surveillance. We also explore the expectations of key stakeholders, including clinicians, patients, regulatory bodies and industry, and discuss unresolved challenges such as explainability, integration into workflows, reimbursement and environmental sustainability. By aligning innovation with ethical and clinical priorities, AI holds the potential to redefine IBD care. Its future will be shaped by collaboration, transparency and responsible implementation, ushering in a new era of personalized, efficient and equitable care for individuals with IBD.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Artificial intelligence in inflammatory bowel disease: bridging innovation, implementation and impact

  • 期刊论文

  • 发表日期：

    2026年3月19日

查看全文
  • Marietta Iacucci,
  • Giovanni Santacroce,
  • Yasuharu Maeda,
  • Snehali Majumder,
  • Cesare Hassan,
  • Dennis L. Shung,
  • Ryan W. Stidham,
  • Raf Bisschops,
  • Valery Naranjo,
  • Enrico Grisan,
  • Subrata Ghosh

摘要

Artificial intelligence (AI) is rapidly transforming the management landscape of inflammatory bowel disease (IBD). While early applications in endoscopy, digital pathology and cross-sectional imaging drew substantial attention, next-generation AI systems that enable deeper disease understanding, personalized treatment and streamlined clinical workflows are now emerging. These advances encompass the multimodal integration of endoscopic, histological and molecular data (‘endo-histo-omics’); AI-assisted assessment of the intestinal barrier; remote monitoring via wearables; and the incorporation of large language models for decision-making support and patient interactions. This Perspective traces the evolution of AI in IBD from domain-specific tools to foundational platforms supporting data-driven precision medicine. We highlight validated AI applications across diagnosis, monitoring, outcome prediction and neoplasia surveillance. We also explore the expectations of key stakeholders, including clinicians, patients, regulatory bodies and industry, and discuss unresolved challenges such as explainability, integration into workflows, reimbursement and environmental sustainability. By aligning innovation with ethical and clinical priorities, AI holds the potential to redefine IBD care. Its future will be shaped by collaboration, transparency and responsible implementation, ushering in a new era of personalized, efficient and equitable care for individuals with IBD.