TY - JOUR
T1 - Artificial Intelligence–Driven Personalized Medicine
T2 - Transforming Clinical Practice in Inflammatory Bowel Disease
AU - Iacucci, Marietta
AU - Santacroce, Giovanni
AU - Yasuharu, Maeda
AU - Ghosh, Subrata
N1 - Publisher Copyright:
© 2025 The Authors
PY - 2025/8
Y1 - 2025/8
N2 - Inflammatory bowel disease is marked by significant clinical heterogeneity, posing challenges for accurate diagnosis and personalized treatment strategies. Conventional approaches, such as endoscopy and histology, often fail to adequately and accurately predict medium- and long-term outcomes, leading to suboptimal patient management. Artificial intelligence is emerging as a transformative force enabling standardized, accurate, and timely disease assessment and outcome prediction, including therapeutic response. Artificial intelligence–driven intestinal barrier healing assessment provides novel insights into deep healing, facilitating the discovery of novel therapeutic targets. In addition, the automated integration of multi-omics data can enhance patient profiling and personalized management strategies. The future of inflammatory bowel disease care lies in the artificial intelligence–enabled “endo-histo-omics” integrative real-time approach, harmoniously fusing endoscopic, histologic, and molecular data. Despite challenges in its adoption, this paradigm shift has the potential to refine risk stratification, improve therapeutic precision, and enable personalized interventions, ultimately advancing the implementation of precision medicine in routine clinical practice.
AB - Inflammatory bowel disease is marked by significant clinical heterogeneity, posing challenges for accurate diagnosis and personalized treatment strategies. Conventional approaches, such as endoscopy and histology, often fail to adequately and accurately predict medium- and long-term outcomes, leading to suboptimal patient management. Artificial intelligence is emerging as a transformative force enabling standardized, accurate, and timely disease assessment and outcome prediction, including therapeutic response. Artificial intelligence–driven intestinal barrier healing assessment provides novel insights into deep healing, facilitating the discovery of novel therapeutic targets. In addition, the automated integration of multi-omics data can enhance patient profiling and personalized management strategies. The future of inflammatory bowel disease care lies in the artificial intelligence–enabled “endo-histo-omics” integrative real-time approach, harmoniously fusing endoscopic, histologic, and molecular data. Despite challenges in its adoption, this paradigm shift has the potential to refine risk stratification, improve therapeutic precision, and enable personalized interventions, ultimately advancing the implementation of precision medicine in routine clinical practice.
KW - Advanced Endoscopy
KW - Barrier Healing
KW - Digital Pathology
KW - Machine Learning
UR - https://www.scopus.com/pages/publications/105004800588
U2 - 10.1053/j.gastro.2025.03.005
DO - 10.1053/j.gastro.2025.03.005
M3 - Article
C2 - 40074186
AN - SCOPUS:105004800588
SN - 0016-5085
VL - 169
SP - 416
EP - 431
JO - Gastroenterology
JF - Gastroenterology
IS - 3
ER -